I'm using Claude to build a custom wireless sync solution for my Kobo reader. Cool, yeah. And possible because I'm basically already a software developer. But if anyone thinks 'normal people' are going to start building their own apps or whatever, let me tell you: you are dreaming. No chance anyone else is going to sit through two hours of this. None.
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993 results for “thro”
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We, the Hated review – standing up to be abused: behind the scenes with Just Stop Oil
By Cath ClarkeThe levels of violence aimed at these protesters is depressing, but their aim is to save the planet: ‘If they want to destroy everything, they’ve got to go through us’
#Film #Documentaryfilms #JustStopOil #Protest #Culture #Environment #Worldnews #TheGuardian #CathClarke
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Google quietly updated its privacy policy to allow data from your Gmail, Drive, and Photos to be used for targeted ads, provided you've enabled certain AI personalization features https://alternativeto.net/news/2026/10/google-may-now-use-your-gmail-and-photos-data-to-serve-targeted-ads-through-ai-search/
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Salta Extended
(Jose E. Robayo Moreno, 2026)🕹️ Play online:
https://www.file-hunter.com/MSXdev/?id=salta📥 Download:
https://www.msxdev.org/2026/10/25/msxdev26-11-salta-extended/Salta Extended is an assembly remake of a 1986 type-in BASIC game. You run home from right to left, jumping over ground obstacles and dodging flying or thrown enemies, with a smooth parallax scrolling background added to the classic runner.
#msx #MSXGames #retrogaming #retrogames
(Video: MSXDev) -
After playing around with my Himi set over the last 10 months, overall I'm pretty mixed about the popular "jelly gouache" paints.
On the plus side, they're cheap and do the job. The Himi container is nice and durable, and it's a pretty convenient setup with paints, a few brushes and a nice big palette. It does the trick, and it's definitely a nice intro to gouache painting.
At the same time, the concept seems pretty flawed because the paints can grow moldy over time. If the colors dry up they lose that creamy gouache feel, but if you put them away too damp then you're creating and ideal environment for mold to develop.
Maybe this is something that isn't a problem if you use the paints up quickly, but I've now had to throw away 2 entire colors because they developed a layer of mold. I wonder if the famous Nicker poster colors suffer from this same issue too over time? [1/2]
#art #artsupplies #painting #paints #gouache #himi #jellygouache
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“All it takes is just a little change of perspective and you begin to see a whole new world”*…
… and we could all use a change of perspective…
Ambient Earth is a 7.5-hour, real-time, 4K, remastered video of the orbital view from the International Space Station. Seán Doran took almost 49,000 images from 27 time-lapse sequences captured from the ISS by astronaut Butch Wilmore, repaired, remastered, and interpolated them into this incredible video.
Perspective is lost when the world speeds by. The scale and beauty of our home planet is truly appreciated when observed on an epic 7.5 hour journey from The International Space Station. This ambitious 4k compilation, crafted through months of meticulous restoration, invites you to slow down and experience Earth in real time just as astronauts do.
The video is accompanied by ambient audio recorded on the station by Chris Hadfield…
https://youtu.be/alJMoaKpV_E?si=Z3S_VzKDpxguWtKK
A pause that refreshes– and reframes: “Ambient Earth” via @kottke.org.
* Bob Ross
###
As we see the big picture, we might we might spare a thought for Ulugh Beg; he died on this date in 1449. Probably the greatest scientist in Mongolia’s history, Beg was a Timurid ruler and sultan, a mathematician, and the greatest astronomer of his time. In his observatory at Samarkand he discovered a number of errors in the computations of the 2nd-century Alexandrian astronomer Ptolemy, whose figures were still being used; his star map (of 994 stars) was the first since Hipparchus‘ (c. 135 BCE).
Ulugh Beg in a contemporary Timurid painting, 1425–1450 (source) #astronomy #culture #earth #history #InternationalSpaceStation #ISS #Science #starMap #UlughBeg -
Hamas said airstrikes carried out by the zionist occupation army on the Islamic University campus in #Gaza City martyred three university staff members and wounded several others while students were present. The movement characterized the strike as a war crime and an extension of an ongoing genocide lasting more than three years, accusing the enemy government of violating the ceasefire agreement through daily bombardment of residential neighborhoods, displacement tents, and civilian institutions, as well as advancing the yellow line westward to seize land and blocking basic food supplies.
Hamas called on mediators and the agreement's guarantor nations to intervene immediately and pressure the occupation to halt its actions against civilians, lift the siege, and deliver aid to more than two million people.
25/10/2026
https://t.me/Palresistmirror/97396#IsraelWarCrimes #warcrimes #IsraelTerroristState #hunger #CeasefireViolations #palestine
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Everyone has a retry story. Mine: an agent that retried a malformed request eleven times before anyone noticed, each attempt replaying the full conversation. The request was never going to succeed — a 400 doesn't heal — but the retry policy didn't care, because it only looked at "did it throw?"
Our working rules now:
- Retry timeouts, 429s and 5xx — with backoff, jitter, and the server's
Retry-Afterwinning over our schedule. - Never retry 400/401/403. Fail fast, surface it, fix the request.
- A retry budget, not just a count: retries get a slice of the task's total budget, then the task fails honestly.
- If it dies mid-stream, restart the message cleanly — never append to a half-generated answer.
What I haven't settled: provider 529s / overloaded errors during peak. Retry in place, or fail over to a different model immediately and accept the quality change?
What's your rule set — and which error taught it to you?#ai #llm #discuss #api #software #coding #development #engineering #inclusive #community
What's your rule for when an LLM call should NOT be retried? - Retry timeouts, 429s and 5xx — with backoff, jitter, and the server's
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PyTorch Low-Level Primitives vs. Agent Framework Abstractions
Framework abstractions are useful until your inference latency spikes by 400 milliseconds, memory leaks across recursive runs, and you have zero visibility into the execution stack.In the rush to build autonomous AI applications, many engineering teams wrap their entire business logic in heavy multi-layer orchestrators before understanding the underlying computation. When an unhandled recursion occurs or memory leaks in long-running processes, debugging third-party wrapper classes becomes substantially more expensive than writing native code.
Here is an architectural breakdown of why engineers must understand low-level PyTorch primitives before relying on high-level framework wrappers.
1. The Cost of Framework Indirection
When you call an LLM through three nested framework wrappers:# Multi-layer wrapper abstraction
agent = AgentExecutor(
chain=LLMChain(llm=ChatOpenAI(), prompt=PromptTemplate(...)),
tools=[SearchTool(), SQLTool()],
memory=ConversationBufferMemory()
)You inherit:
- Hidden Call Stacks: 30+ frames of traceback obfuscating basic HTTP request errors or malformed payload dictionaries.
- Context Bloat: Default framework memories serialize entire objects, rapidly exhausting model context windows and inflating token costs.
- Execution Lag: Unnecessary serialization and deserialization cycles between proprietary wrapper classes.
2. Core PyTorch Primitives Every AI Engineer Must Understand
Understanding core PyTorch primitives—such as tensor layouts, attention masks, KV-caching mechanics, and CUDA stream concurrency—gives engineers the diagnostic capability to build reliable systems:A. Tensor Memory Layouts & Stride Arithmetic
Tensors are not generic Python lists. They are continuous blocks of memory defined by shapes and strides. When batching prompts of variable lengths:- Improper padding degrades throughput.
- Non-contiguous memory layouts force expensive hidden copy operations.
- Understanding contiguous memory and views (
tensor.view()vstensor.reshape()) is critical for optimizing custom inference runtimes.
B. KV-Cache Allocation & VRAM Arithmetic
In autoregressive generation, computing self-attention across previous tokens at every step is $O(N^2)$. Modern inference engines cache the Key and Value matrices (KV-cache).- For a 70B parameter model at 16-bit precision, KV-cache consumption scales directly with batch size and context window length.
- Engineers who understand KV-cache memory mathematics can calculate exact concurrency thresholds before an out-of-memory (OOM) event crashes a GPU container.
C. Attention Masks & Scaled Dot-Product Computation
Attention(Q, K, V) = softmax( (Q * K^T) / sqrt(d_k) ) * VUnderstanding FlashAttention and kernel fusion allows you to diagnose why a local model is bottlenecked by memory bandwidth rather than compute power.
3. The Recommended Architecture Hierarchy
+-------------------------------------------------------------+
| Layer 3: Lightweight State Orchestration (LangGraph / Native)|
| - Explicit state transitions & cyclic routers |
| - Strict Pydantic / Zod argument schemas |
+-------------------------------------------------------------+
|
v
+-------------------------------------------------------------+
| Layer 2: High-Performance Serving (vLLM / TensorRT-LLM) |
| - PagedAttention (Memory fragmentation elimination)|
| - Continuous batching & asynchronous token streams |
+-------------------------------------------------------------+
|
v
+-------------------------------------------------------------+
| Layer 1: Native PyTorch & CUDA Execution Primitives |
| - Half-precision tensor arithmetic (FP16 / BF16) |
| - Kernel fusion & direct memory management |
+-------------------------------------------------------------+4. Final Verdict
Frameworks should be adopted to accelerate standard integration pipelines—not as a substitute for understanding execution mechanics.When you master low-level primitives:
- You optimize batch inference latency by 3x to 5x.
- You eliminate mysterious GPU out-of-memory errors in production.
- You build lean, deterministic systems that your clients can rely on 24/7.
Are you running direct model runtimes (vLLM, TensorRT-LLM, Ollama) or relying on multi-layer orchestration libraries?
Authored by Soham Sharma, Founder & Director at Botmartz AI Solutions.#ai #python #machinelearning #architecture #software #coding #development #engineering #inclusive #community
PyTorch Low-Level Primitives vs. Agent Framework Abstractions -
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Tru2Day2761
My kindness is strictly reserved for innocent babies and animals, because ninety-nine percent of adults are absolute trash. Anyone heartless enough to abandon their aging parents in a nursing home instead of honoring them is completely rotten to the core. If they can throw away the people who raised them, they're pure evil. -
Hawthorne is not an author I am familiar with, and it doesn’t sound like I would enjoy his macabre writing. But it was fun getting a glimpse of some of the little fragments he wrote in his notebooks.
(Not sure I would want someone rifling through the fragments I write in my notebooks!!)
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The 3 Phases of Holiday Book Sales (and How to Win Each One)
Listen & Subscribe: Apple Podcasts Spotify YouTube About the Episode: The holiday season isn’t just one big shopping rush; it’s three distinct marketing windows, and indie authors can win all three. In this episode, Ricci and Ferol break down the full holiday timeline, from Black Friday through mid-January, and give you a concrete plan for […]
The post The 3 Phases of Holiday Book Sales (and How to Win Each One) appeared first on Written Word Media.
https://www.writtenwordmedia.com/the-3-phases-of-holiday-book-sales-and-how-to-win-each-one/ -
I wanted to create a 60-second cinematic FPV travel film across the United States, moving from New York to San Francisco and Los Angeles.
The goal wasn't simply to generate impressive AI footage. I wanted the entire film to feel like one continuous drone journey rather than a collection of unrelated clips stitched together in post-production.
That introduced three practical challenges:
- Maintaining visual continuity across independently generated clips.
- Controlling camera movement, lighting, and transitions through prompts.
- Fixing individual shots without regenerating the entire video.
I built the film using GMI Cloud's video generation models, frame chaining, and FFmpeg.
The final output was exactly 60 seconds long, rendered at 1080p, with a targeted replacement for a shot that generated incorrectly.
Here's how the pipeline worked, including the API issues, failed generations, and techniques that made the workflow more reliable.
1. Understanding the Duration Constraint
The first step was checking the available models and their actual generation limits.Rather than relying on model names or assumptions, I used GMI Cloud's
get_modeltool to inspect the supported parameters, duration limits, and pricing.get_model({ model_id: "seedance-2-5-260628" })
get_model({ model_id: "wan3.0-video" })
get_model({ model_id: "veo-3.1-generate-001" })The following figures reflect the catalog and pricing I observed during development in October 2026. Verify them against the current catalog before using them in production.
ModelMaximum durationObserved 1080p price/secRelevant capabilitiesseedance-2-5-26062830 seconds$0.569First-frame and last-frame conditioning, reference images, audio generationwan3.0-video30 seconds$0.20Frame conditioning, reference images, separate negative promptveo-3.1-generate-0018 seconds$0.40High photorealism, two-frame conditioningkling-3.0-turbo-t2v15 seconds$0.14Text-to-video generationseedance-2-0-260128-upscale15 seconds$0.056Budget-oriented optionveo-3.1-lite-generate-0018 seconds$0.05Lower-cost generation at supported resolutions
These capabilities and prices are model- and configuration-dependent. Check the current API schema before building around a particular parameter.The key constraint was straightforward: no model in this selection could generate the entire 60-second film in one request.
I therefore split the project into two 30-second generations.
Fewer, longer clips reduce the number of boundaries that need to be managed. A six-clip pipeline introduces five joins, while a two-clip pipeline introduces just one.
However, clip length shouldn't be the only consideration. The structure of the film matters, too. If a story naturally contains three distinct locations or sequences, three shorter clips may be easier to control than two longer generations.
The objective is to minimize unnecessary joins without forcing unrelated scenes into one generation.
2. Prompt Engineering: Control the Camera Before the Scene
One of the biggest lessons from this project was that a video prompt needs to describe motion, not just visual content.My initial prompts combined several events into short sequences:
- Dive between skyscrapers.
- Sweep toward the Hudson River.
- Transition from sunrise to blue hour.
- Race through city streets.
- Introduce light trails.
The results were inconsistent. Architecture distorted, transitions became muddy, and the camera sometimes appeared to blend incompatible locations.
The problem was trying to control too many independent events in a single prompt.
My revised approach was to define a continuous camera movement with explicit scene timing.
The single-movement principle
Describe one continuous camera journey per generation, and use FFmpeg for editorial cuts.This doesn't mean a longer generation must contain only one location. It means the transitions between locations should follow a physically understandable camera movement rather than asking the model to perform several unrelated edits.
For example, an aircraft wing can pass across the lens and temporarily obscure the entire frame. The next location can emerge as the wing clears.
That provides a visual transition the model can attempt to render as part of the camera movement.
Here's an excerpt from the prompt used for the film:
Ultra-realistic cinematic FPV drone travel film, 30 seconds, 16:9.
One continuous high-speed journey across the United States.
Maintain forward camera momentum throughout.Photorealistic imagery, consistent teal-and-orange commercial
color grading, high dynamic range, natural film grain,
subtle horizontal anamorphic lens flare, and a wide 14mm lens.Use smooth motion blur only during the fastest movements.
No text, captions, subtitles, logos, watermarks, or readable
signage.SHOT 1 (0-7s):
Above New York City at sunrise. Low mist surrounds the
skyscrapers as the drone tips forward and dives between
glass towers. Golden light reflects across the facades.SHOT 2 (7-15s):
The camera descends to street level and races down a wide
Manhattan avenue. Moving cars pass beneath the camera,
their headlights and taillights creating flowing light trails.SHOT 3 (15-22s):
The drone rises over New York Harbor. A ferry crosses the
water below, leaving a white wake. The camera sweeps around
to reveal the Statue of Liberty in the morning haze.SHOT 4 (22-30s):
An aircraft wing passes directly across the lens, filling
the frame. As it clears, the camera emerges above turquoise
Pacific water near San Francisco, moving toward the Golden
Gate Bridge as its red towers appear through coastal fog.The timing provides structure, but it doesn't guarantee that the model will follow every boundary precisely. Treat shot durations as guidance and inspect the generated footage before editing.
Keep the visual identity consistent
Consistency doesn't require identical lighting throughout the film.The sequence moves between sunrise, daylight, golden hour, and night. Those changes are part of the story.
What should remain relatively stable is the visual treatment:
- Color grading.
- Lens characteristics.
- Motion style.
- Contrast and highlight handling.
- Overall level of realism.
I repeated the same visual descriptors across prompts while allowing the lighting and environment to change.
This gave the film a more consistent look without making every location feel artificially identical.
Negative prompts are model-specific
Different models expose different controls.For example,
wan3.0-videosupports a dedicatednegative_promptparameter, while the Seedance 2.5 configuration I used did not expose that parameter.For Seedance, I placed unwanted elements directly in the prompt:
No text, captions, subtitles, logos, watermarks, or readable
signage anywhere in the frame.The general lesson is to inspect the actual model schema rather than assume that every video model supports the same parameters.
3. Frame Chaining: Maintaining Continuity Between Clips
Frame chaining was the central technique in this project.Instead of generating two unrelated clips and trying to hide their differences afterward, I used the final frame of the first clip to condition the beginning of the second.
The pipeline is simple:
- Generate clip A.
- Extract a frame near the end of clip A.
- Upload the frame to GMI Cloud.
- Pass its URL as the
first_frameparameter when generating clip B. - Inspect the boundary and adjust the edit if necessary.
The second generation now has a visual reference for where the first generation ended.
Extracting the frame with FFmpeg
I extracted a frame near the end of the first clip:ffmpeg -y -ss 29.9 -i clipA.mp4 \
-frames:v 1 chain_last.pngI then normalized the image to the intended output dimensions and converted it to JPEG:
ffmpeg -y -i chain_last.png \
-vf "scale=1920:1080:force_original_aspect_ratio=increase,crop=1920:1080" \
-q:v 3 chain_first.jpgThe output dimensions should match the intended video aspect ratio. If the source frame already has the correct dimensions, unnecessary scaling and cropping can be avoided.
The extracted image becomes the conditioning frame for the next generation.
Uploading the frame to GMI Cloud
Theupload_mediaoperation returns a signedupload_urland apublic_url.These serve different purposes:
upload_urlis the destination for uploading the file.public_urlis the image URL supplied to the video generation request.
The signed URL doesn't upload the file automatically. You must send the image bytes to it.
Here's a minimal Python example:
import urllib.request
upload_url = "<upload_url from upload_media>"
with open("chain_first.jpg", "rb") as image_file:
image_data = image_file.read()request = urllib.request.Request(
upload_url,
data=image_data,
method="PUT",
headers={"Content-Type": "image/jpeg"},
)with urllib.request.urlopen(request) as response:
print(response.status)Use the URL and HTTP method specified by the upload operation. If the signed URL expires or the upload returns a signature error, request a fresh URL and retry.
I encountered a
403 SignatureDoesNotMatcherror with an earlier upload URL. Requesting a new URL resolved the problem in my case.Generating the next clip
With the frame uploaded, I passed its public URL to Seedance 2.5.The following is a representative request structure; use the exact field names and request envelope documented by the current API.
{
"model_id": "seedance-2-5-260628",
"prompt": "<your scene and camera-movement prompt>",
"parameters": {
"duration": 30,
"resolution": "1080p",
"ratio": "adaptive",
"first_frame": "<public_url of chain_first.jpg>",
"generate_audio": true,
"watermark": false
}
}The critical setting was
ratio.The
ratioconfiguration issue
I encountered failed generations when using an explicitratio: "16:9"and when omitting the ratio entirely.The API returned an error explaining that, when first-frame or first-and-last-frame conditioning is used, the output aspect ratio follows the input frame.
The configuration that worked was:
"ratio": "adaptive"
For this particular model configuration, using
ratio: "adaptive"resolved the issue.Don't assume that a parameter's default value is valid for every generation mode. Frame-conditioned generation can have different validation rules from text-to-video generation.
Verify this behavior against the current API documentation before relying on it in another model version.
What frame chaining actually guarantees
Frame chaining is useful, but it is important to distinguish three different forms of continuity.Frame continuity: The next generation receives a reference image matching the preceding clip's endpoint.
Temporal continuity: Camera motion, object movement, lighting, and perspective evolve naturally across the boundary.
Subject continuity: People, vehicles, and other objects maintain their identity and appearance across shots.
Frame chaining primarily addresses the first problem. It can help with the second, but it doesn't guarantee a perfect motion transition. It also doesn't guarantee subject consistency across independently generated scenes.
A matching boundary frame is not proof that the surrounding motion will be seamless.
For recurring subjects, combine frame conditioning with reference images where the model supports them.
ModelReference parameterObserved catalog limitwan3.0-videoreference_image,reference_videoUp to 10 images and 5 videosseedance-2-5-260628reference_images,reference_videosUp to 9 images and 3 videoshappyhorse-1.1-r2vreference_imageUp to 5 images
These limits are model-specific and should be verified before use.I also found that frame chaining works best when the next clip continues a compatible scene.
A coastline transitioning into a bridge approach provides a natural continuation. A sudden jump from San Francisco to a Los Angeles street is a different editorial event and is often better handled as a deliberate cut.
Chain compatible camera movements. Use editing to handle genuine changes in scene or location.
4. Stitching the Film with FFmpeg
Once the clips were generated, I assembled them into the final video.For a simple join, FFmpeg's concat demuxer is convenient when the input files have compatible stream properties.
Create a file named
list.txt:file 'clipA.mp4'
file 'clipB.mp4'Then concatenate the clips:
ffmpeg -y -f concat -safe 0 -i list.txt \
-t 60.0 \
-vf "fps=24,scale=1920:1080:flags=lanczos,format=yuv420p" \
-c:v libx264 -preset slow -crf 17 \
-c:a aac -movflags +faststart \
out/master.mp4This example assumes that the input streams are compatible with the chosen filter and encoding pipeline. Incompatible codecs, time bases, resolutions, or audio streams may require normalization before concatenation.
The command also re-encodes the video, so it is not a lossless join.
When the clips need different processing
For the final replacement, I needed to combine a 50-second section of the existing master with a newly generated 10-second clip.I used a filter graph to concatenate the video and audio streams while normalizing the video output:
ffmpeg -y -i head.mp4 -i clipFix.mp4 \
-filter_complex \
"[0:v][1:v]concat=n=2:v=1:a=0,fps=24,scale=1920:1080:flags=lanczos,format=yuv420p[v]; \
[0:a][1:a]concat=n=2:v=0:a=1[a]" \
-map "[v]" -map "[a]" \
-t 60.0 \
-c:v libx264 -preset slow -crf 17 \
-profile:v high -level 4.2 \
-c:a aac -b:a 192k \
-movflags +faststart \
out/america_60s_16x9_v2.mp4This version assumes both inputs contain compatible audio streams. If one clip lacks audio, the filter graph needs to be adjusted to create or omit the missing stream.
Also,
-t 60.0limits the output duration; it doesn't independently guarantee that the final file contains exactly 60 seconds of usable footage.To verify the result, inspect the actual duration and frame count.
ffprobe -v error \
-show_entries format=duration \
-of default=noprint_wrappers=1:nokey=1 \
out/america_60s_16x9_v2.mp4For a 24 fps output, 60 seconds corresponds to 1,440 frames. Checking both duration and frame count is useful when exact delivery specifications matter.
Creating a cinematic 2.39:1 presentation
The source video was generated at 16:9, but I also wanted to test a wider cinematic presentation.One option is to scale the image to 1920 × 804 and add black bars to restore a 1920 × 1080 canvas:
ffmpeg -y -i master.mp4 \
-vf "scale=1920:804:flags=lanczos,pad=1920:1080:0:138:black" \
-c:v libx264 -preset slow -crf 17 \
-profile:v high \
-c:a copy \
-movflags +faststart \
out/master_239.mp4This produces an approximately 2.39:1 image area within a 16:9 video frame.
Letterboxing preserves the entire scaled image, unlike a direct vertical crop that discards parts of the original frame.
However, scaling the full 16:9 image to 1920 × 804 changes its proportions unless the image is cropped first. For a geometrically correct widescreen presentation, use a crop-and-scale pipeline when necessary.
5. Re-Rendering One Bad Shot Instead of the Entire Film
One of the most useful aspects of this workflow was the ability to replace a specific segment without rebuilding the whole video.During generation, the Hollywood sign appeared as "HOLFWOOD" instead of "HOLLYWOOD".
This is a familiar limitation of generative video models: text can look convincing at a glance while individual characters remain incorrect or unstable.
Regenerating the entire 60-second film would have wasted both time and credits.
Instead, I extracted the frame at the replacement boundary, used it as the new clip's
first_frame, and generated a replacement segment.ffmpeg -y -ss 50.0 -i out/master.mp4 \
-frames:v 1 splice_first.jpgAfter uploading the frame and generating the replacement clip, I rebuilt the master from the unchanged opening section and the new footage.
The replacement was approximately 10 seconds long.
Prompting for accurate text
For the replacement, I made the lettering requirement explicit:CRITICAL: The hillside sign must read exactly HOLLYWOOD.
The spelling is H-O-L-L-Y-W-O-O-D: nine letters.
The fourth letter must be L, not F.
The letters are large, white, individually formed capital
letters arranged in a straight horizontal line on a dry,
brown hillside.Keep the lettering stable, correctly formed, and clearly
visible from the front. Do not distort, rearrange, or replace
any characters.The revised generation produced the intended spelling.
This doesn't mean literal prompts can reliably solve text rendering in every model. It means a specific description of the expected output and known failure can improve the next attempt.
For shots containing signs, product labels, or other critical text, I recommend treating one or two targeted re-renders as part of the production budget.
When exact typography is essential, a more reliable approach is to add the text during post-production rather than depend on the video model to render it correctly.
6. Practical Issues I Encountered
The creative workflow was only part of the implementation. Several API and environment issues also affected the process.Keep generation parameters in the expected structure
My generation-estimation requests required model-specific parameters to be nested underparameters.For example:
{
"model_id": "seedance-2-5-260628",
"prompt": "<prompt>",
"parameters": {
"duration": 30,
"resolution": "1080p",
"ratio": "adaptive"
}
}Use the structure expected by the relevant operation. An estimation endpoint and a generation endpoint may not accept identical request bodies.
An MCP timeout doesn't necessarily mean generation failed
Onesubmit_generationrequest timed out on the client side while the server-side generation continued running.Submitting the same request again could have created unnecessary work or additional charges.
Instead, I used
list_generationsto inspect the existing jobs and recover their status.For production systems, keep track of generation IDs, request parameters, and job status. When supported, use idempotency controls to distinguish intentional re-renders from accidental duplicate submissions.
Check which credits apply to each model
My account displayed a zero-dollar balance alongside promotional credits. One model returned aninsufficient_balanceerror, while another accepted the request.This was an account-specific result, not proof that all promotional credits are restricted in the same way.
Before running a large batch, verify that the available credits apply to the selected model and generation configuration.
Verify your FFmpeg version
My system FFmpeg installation was too old to handle the HEVC Main10 output produced by the video model.The resulting codec errors initially looked like a problem with the downloaded file.
I installed a newer FFmpeg binary through
imageio-ffmpeg:pip install imageio-ffmpeg
Then I checked the binary path:
python -c "import imageio_ffmpeg; print(imageio_ffmpeg.get_ffmpeg_exe())"
Use a sufficiently recent FFmpeg build with the codecs required by your source footage.
For reproducible workflows, check the installed version and codec support before beginning a batch of generations.
Verify audio instead of trusting the response
Although I requested audio generation, both clips returned valid AAC audio streams that were effectively silent.I checked the audio levels with:
ffmpeg -i clip.mp4 \
-af volumedetect \
-f null - 2>&1 | grep -E "mean_volume|max_volume"A valid audio stream doesn't necessarily contain audible sound. Inspect the output and listen to the actual result before delivery.
Separate language-model usage from media-generation costs
The account-summary information I inspected reported language-model usage separately from image and video generation.Don't treat an LLM token-cost report as a complete accounting of a media-generation project.
Track the actual generation requests and their associated charges, and reconcile them against the relevant billing information.
7. Cost Breakdown
GenerationDurationObserved costClip A — Seedance 2.5, 1080p30 seconds$17.07Clip B — Seedance 2.5, 1080p, frame-conditioned30 seconds$17.07Replacement clip — Seedance 2.5, 1080p10 seconds$5.69Total70 generated seconds$39.83
The final film used two 30-second clips and one 10-second replacement.
The total cost was $39.83 for a final 60-second film.Notice that the generation duration adds up to 70 seconds, not 60. The extra 10 seconds came from replacing the incorrect segment.
The effective cost was approximately $0.66 per second of finished video.
These figures reflect the pricing and usage observed during this project. They exclude any additional costs not reflected in the recorded generation charges.
A lower-cost model may make experimentation more affordable, but cheaper generation can also require additional attempts to reach the desired visual quality.
The right choice depends on the importance of photorealism, continuity, generation speed, and budget.
Budget for re-renders from the beginning. A pipeline that assumes every generated shot will be usable is likely to underestimate its actual cost.
8. Scaling the Pipeline Beyond 60 Seconds
The same approach can be extended to longer films.At a maximum of 30 seconds per clip:
Final durationNumber of clipsNumber of joins60 seconds213 minutes655 minutes10910 minutes2019
These counts assume full-length 30-second clips. Shorter clips may be more appropriate when the story contains distinct scenes or requires tighter control.Each additional join creates another opportunity for mismatched motion, lighting, composition, or subject appearance.
Several practices make a longer pipeline easier to manage.
Choose boundary frames deliberately
Don't extract the final frame automatically without checking it.Look for a frame where the camera is passing behind an object, approaching a new landmark, or entering a natural visual transition.
These moments can make an editorial boundary less noticeable.
However, the extracted frame should also provide a useful starting composition for the next generation. A visually interesting boundary is not necessarily a good conditioning frame if the next scene cannot continue naturally from it.
Preserve intermediate frames and generation metadata
Archive the conditioning frame used for every clip, along with:- The original prompt.
- Model ID and generation parameters.
- Generation job ID.
- Source and output file paths.
- Cost and duration.
- Notes about failed attempts.
If clip 4 needs to be regenerated, the saved endpoint from clip 3 allows you to reproduce its starting condition without rebuilding the earlier footage.
This makes the workflow easier to debug and maintain.
Parallelize independent generations
Once the necessary reference frames are available, independent segments can be generated concurrently.A fully sequential chain cannot be generated entirely in parallel because each clip may depend on the preceding clip's output.
A practical compromise is to divide the film into sequences that can be generated independently, then chain clips within each sequence.
Use idempotency controls where supported, and check the job list before retrying a timed-out request.
Make every segment independently replaceable
Treat each generated clip as a separate production asset.The master video should be a reproducible output of the individual segments and the editing pipeline, not the only copy of the project.
That allows a single failed shot to be replaced without rebuilding the entire film.
9. Visual Verification Before Delivery
A successful API response doesn't mean the video is ready to publish.I used FFmpeg to extract representative frames from across the timeline and assemble them into a contact sheet.
This made it easier to identify changes in visual style, unexpected objects, and problems with transitions.
For example, to inspect eight points in the film:
mkdir -p keys
for t in 1 9 17 25 33 41 49 58; do
ffmpeg -y -ss "$t" -i out/master.mp4 \
-frames:v 1 \
-vf "scale=470:-1" \
"keys/m_${t}.jpg"
doneThe individual frames can then be assembled into a contact sheet.
A contact sheet is useful for reviewing the overall visual progression, but it won't reveal every temporal artifact.
For that, inspect the actual footage around each join, preferably frame by frame or at reduced playback speed.
For the Hollywood sign, I also extracted frames at half-second intervals to check whether the lettering remained stable throughout the replacement segment.
This helped distinguish incorrect lettering from frames where the sign was partially visible or viewed at an angle.
My final verification checklist included:
- [ ] Confirm the final duration and frame rate.
- [ ] Inspect every join for jumps in camera position or motion.
- [ ] Check lighting, color grading, and scene continuity.
- [ ] Review text, faces, architecture, and other high-risk details.
- [ ] Verify audio levels and playback.
- [ ] Confirm the output resolution and encoding.
- [ ] Play the final exported file from beginning to end.
The model generates the footage. The editing and verification pipeline determines whether it is ready to ship.
Conclusion
Building a continuous AI-generated film is not just a prompting problem. It is a pipeline problem involving generation limits, frame conditioning, asset management, editing, and quality control.For this project, frame chaining provided a practical way to connect separately generated clips while keeping each segment independently replaceable.
The most important lessons were:
- Check model capabilities before designing the pipeline. Generation limits and parameter support determine how the film should be structured.
- Describe camera movement explicitly. A coherent camera path is easier to manage than a prompt containing unrelated transitions.
- Use frame chaining for continuity. The previous clip's endpoint provides a visual starting condition for the next generation.
- Keep the pipeline modular. Replace failed segments rather than regenerating the entire film.
- Verify the actual output. Inspect the joins, text, audio, duration, and final encoding.
- Budget for failed generations. Re-renders are part of the workflow, not an unexpected exception.
The final film cost $39.83 in recorded generation charges and required 70 seconds of generated footage to produce 60 seconds of finished video.
The broader takeaway is that AI video generation becomes more manageable when treated as a reproducible media pipeline rather than a sequence of isolated prompts.
Frame chaining won't eliminate every continuity problem, but it gives you a useful degree of control over how separately generated footage fits together.
Model capabilities, parameter support, and pricing are subject to change. The figures in this article reflect observations from October 2026. Check the current GMI Cloud model catalog and API documentation before implementing the workflow.#ai #tutorial #beginners #showdev #software #coding #development #engineering #inclusive #community
Frame-Chaining AI Video: Building a 60-Second Film with GMI Cloud -
Kansas Republicans have been single-mindedly focused in recent years on passing anti-trans legislation into law.
To block future anti-trans laws, Democrats need to win the Governor’s Race, and break the Republican Supermajority in the Kansas Legislature.
If Republicans win the Governor’s Race, only a simple majority would be needed to pass anti-trans legislation through the Kansas Legislature, which Republicans will easily be able to do.
39/x
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The Rise of AI: Is There Hope for Mankind?
Extraordinary advances in artificial intelligence fuel dreams of ease on one hand, and nightmares of catastrophe on the other. Will AI supplant human decision-making? Will humanity even survive?
The Rise of AI: Is There Hope for Mankind?
by Steven Britt
ince the release of ChatGPT in late 2022, the world has been captivated by advances in the field of artificial intelligence (AI). As these systems become more humanlike in their output, everyone—from leading experts in the field to presidents and pundits alike—is feeling the accelerated pace of technology and wondering where we are headed.
In 2023, Elon Musk warned, “AI is more dangerous than, say, mismanaged aircraft design or production maintenance or bad car production . . . It has the potential of civilization destruction” (emphasis added throughout).
Is there reason to fear AI? Is it possible that AI will soon achieve human-level or even superhuman intelligence? And, if so, is there hope for mankind to survive the creation and implementation of such a powerful technology?
When machines learn to think
While the AI we see today is impressive, many experts believe we are only a few years away from artificial general intelligence (AGI)—systems with the humanlike ability to solve entirely new problems by innovation, experimentation and learning.
Since the inception of the machine age, computer software has only been able to accomplish rigid, preprogrammed instructions within strict boundaries. However, AI is now able, without a single line of new code, to perform a multitude of tasks on request. In minutes, it can make a better diagnosis than your doctor, out-argue a lawyer, translate a speech into another language, negotiate a contract and write a poem about it all in Shakespearian style.
The current reality was nearly unthinkable to the average person just three years ago when ChatGPT debuted. At the time of this writing, AI models are already able to score above average on IQ tests and ace graduate-level exams across multiple disciplines.
Despite these impressive achievements, these systems fall short of AGI.
Intelligence, much like consciousness, is difficult to actually define, and there is no widely accepted definition of exactly what constitutes AGI. Current AI systems perform well on tests because they have likely seen the information before—a distinguishing feature of AGI would be the humanlike ability to solve entirely new challenges, learning and adapting as it goes.
While today’s AI tools can already outperform most human beings on a wide variety of written and verbal tests, a true AGI system would be a world-changing breakthrough. The reason is simple: Machine intelligence can be scaled just by hooking up more processors. One could easily create entire teams of AGIs working together on complex problems from different angles just as people would—researching, experimenting, publishing findings and reasoning. They would never sleep, never take a break, and would operate at superhuman speed.
The first and most obvious task on the agenda, in the minds of many, would be to set this AGI to work unlocking the secrets of building even higher intelligence—redesigning and improving itself until it has completely surpassed human beings, a level known as artificial superintelligence (ASI).
Much thought has gone into the consequences of AGI or ASI becoming a reality, and the imagined outcomes fall into four different possible endings to the story:
1. The A.I. utopia. Guided by careful design and moral wisdom, AGI works tirelessly to end disease, to design and build clean energy grids, and to free humanity to pursue creativity. Work becomes optional, poverty fades and everyone lives happily ever after.
2. The hostile machine. Like the plot of numerous action movies, a rogue AI decides it would be better off without mankind and moves to destroy us.
3. The paperclip maximizer problem. Philosopher Nick Bostrom warned in 2004 that even a neutral AGI can be lethal if it’s simply given the wrong goal. In this scenario, the AGI is set over a factory and told to make as many paperclips as possible. It soon begins converting forests, oceans and eventually human beings into raw materials for more paperclips—inadvertently destroying mankind in a blind pursuit of a poorly defined goal!
4. Human mischief—supercharged. The most likely and earliest danger is abuse of this rapidly changing technology for evil. Just as mid-20th-century physics gave way to nuclear bombs with terrible destructive power, nations or criminals could weaponize and unleash AGI for cyberwarfare, bioweapons and more.
Notice that only one of these outcomes doesn’t end with the destruction of mankind! But will the technologies really advance to such extremes?
2025: The year of AI agents
By the end of 2024, tech leaders were already calling 2025 “the year of AI agents,” signaling a fundamental change in how AI would be used.
Until recently, AI tools like ChatGPT could only generate text and ideas—they could not take real-world action outside of giving a response to a user’s input. AI agents change that completely.
The key difference between a chatbot and an AI agent is that an agent can interface with other software tools, even without being explicitly told to do so, to accomplish a task on its own. The earliest step toward AI agents was adding simple web-search features, allowing AI to perform its own Internet searches, scanning through dozens of different websites to answer detailed queries with up-to-date information.
Significantly, on July 17, 2025, Open-AI released Agent Mode in ChatGPT, imbued with the ability to fully use the Internet through a web browser. For example, you can give Agent Mode the dates of an upcoming trip, your budget and some interests, and it can research the area, plan a full, day-by-day itinerary and book your hotel and tickets for you!
The massive financial bet on AI
If investment is a measure of expectation, the world’s richest companies and governments all clearly believe that AGI—or something similarly world-changing—is coming soon.
In January 2025, OpenAI announced construction of Project Stargate, a $500 billion datacenter requiring over five gigawatts of power—more than twice the output of Hoover Dam. Meanwhile, Elon Musk’s supercomputing center, dubbed Colossus, has cost $4 billion so far and draws 150 megawatts from the grid, with plans to spend $25 billion to quadruple its capacity to nearly 1 gigawatt.
And the spending doesn’t stop at hardware. In one of the most aggressive talent recruiting wars in history, Meta (formerly known as Facebook) has offered elite AI researchers compensation packages worth $300 million per person over four years—sometimes more than $100 million in the first year!
In all this, key chipmaker Nvidia skyrocketed to become the world’s most valuable company in history, topping $4.5 trillion in value.
This “compute race” resembles the nuclear arms buildup of the Cold War, but with one striking difference—the pace. Nuclear weapons development spanned decades; ChatGPT was released just three years ago.
Russian President Vladimir Putin famously said in 2017, “Whoever becomes the leader in AI will become the ruler of the world.” That prediction accurately summed up the fervor for powerful AI systems that has ignited these historic investments.
Biblical perspective: Is AGI really possible?
The fact is, machines cannot replicate the God-given, spiritual nature of human beings. Ecclesiastes 3:11 tells us that God “has put eternity in their hearts.” People are not just biological processors of data. It is the human spirit from our Creator that gives us human understanding (Job 32:8; 1 Corinthians 2:11). And He designed us to live in a loving relationship with Him!
Genesis 2:7 states that “the Lord God formed man of the dust of the ground, and breathed into his nostrils the breath of life; and man became a living being.” AI systems, made of silicon circuits and transistors, are mere dust of the ground.
However, the Bible gives grave warnings about human ingenuity. At the Tower of Babel, God said that, because the people were working together with the same mindset and language, “Nothing that they propose to do will be withheld from them” (Genesis 11:6).
The spread of global technology has helped to remove the language barrier God introduced at Babel. And today’s engineers, corporations and governments are working with one mind and one goal—to create machine intelligence that can learn and perform nearly any task as well as, or better than, human beings.
Gary Kasparov, the renowned chess grandmaster who famously lost to IBM’s Deep Blue chess computer in 1997—a feat once considered impossible for a machine—stated, “Saying that Deep Blue doesn’t really think is like saying an airplane doesn’t really fly because it doesn’t flap its wings.”
In other words, in the eyes of the world the difference between intelligence and capability will be considered irrelevant—as what matters is what AI can do.
Just as the builders at Babel, humanity is coming against limits that once seemed unreachable.
The real dangers start before AGI arrives
Science fiction loves the trope of self-aware AI turning against its creators. Despite the dazzling leaps of AI agents or how human the newest AI models may seem in their writing, they are not at all a step toward true humanlike intelligence.
However, the most immediate dangers of AI do not require any form of consciousness or sentience to amplify evil in the world.
“The heart is deceitful above all things, and desperately wicked; who can know it?” (Jeremiah 17:9).
Recall the problem of “fake news” in recent years. Hundreds of provocative, but untrue, headlines deceived many. AI will be used to produce more convincing content faster than ever, including not only text but fraudulent images and videos that are increasingly difficult to discern.
Likewise, bad actors across the board augment their abilities with AI already—from hackers holding companies hostage with ransomware to phishing scams duping people for their bank information. Very soon, AI agents will make it possible to outsource these evil deeds completely, enabling a single person to deploy as many simultaneous attacks as their computing resources can support.
The scale of the threat grows when considering geopolitical motives. State-sponsored cyber attacks from China against critical U.S. systems are now routine, and their human hackers are probably already equipped with AI assistants at their side. It’s not a stretch to imagine the Chinese government commissioning an army of AI cyberwarfare agents that autonomously seek out vulnerabilities in critical American systems and infiltrate them for espionage and/or disruption.
Internet-based attacks can have real, deadly consequences, but the dangers of AI do not stop there. An Encyclopedia Britannica essay titled “Killer Robots: The Future of War?” postulates that “the first revolution in warfare was the invention of gunpowder. The second was the invention of nuclear weapons. And this [AI-powered autonomous robots] will be the third” (Toby Walsh, Britannica.com, originally published 2018). As it rightly observes, “The weakest link in a drone is the radio link back to base.” Now it can keep going on its own.
Coinciding with developments in AI, drone technology and humanoid robotics have undergone rapid advances in recent years. Flying drones are already redefining the principles of modern warfare through the Russia-Ukraine war, where cheap remote-piloted drones carrying explosives have neutralized multimillion-dollar tanks, dramatically altering battlefield dynamics. Replacing remote drone pilots with AI is an all-but-certain escalation that will soon make these platforms capable of greater destruction and on a much larger scale.
On the robotics front, Boston Dynamics in the U.S. and Unitree Robotics in China are routinely demoing new humanlike and doglike robots—powered by AI systems—that learn via neural networks to not only walk, but run, jump, climb, dance and do backflips. In the near future, governments may be manufacturing vast armies of AI-powered autonomous robot soldiers.
Consider also the problem of AGI or ASI falling into the hands of volatile dictators, and the stakes become even higher. On June 22, 2025, U.S. stealth bombers destroyed three Iranian nuclear facilities, derailing Iran’s uranium enrichment ambitions for years to come. Replace the thought of “uranium enrichment” with “AI computer clusters” and the same logic may apply in the near future—nations launching preemptive strikes to prevent rivals from reaching AI supremacy.
Will humanity survive the AI explosion?
Jesus Christ warned that in the end times the world would be plagued by “wars and rumors of wars” (Matthew 24:6). AI is poised to be both fuel and the spark for that fire.
While AI marches forward at breakneck speed, the “AI utopia” scenario does not seem at all likely. Human nature, as history has shown many times over, dictates that AI will be used as a tool for both good and evil. The abilities of these systems in the near future leave us with very bleak prospects.
Will mankind survive? Jesus said that things will get so bad that “unless those days were shortened, no flesh would be saved [alive] . . .” (Matthew 24:22). In other words, the Bible confirms that the doom-and-gloom scenarios are indeed the logical, predictable outcome of man’s efforts!
Our greatest problems—war, greed, corruption—are not technical but spiritual in nature. AI cannot solve them. Rather, it will amplify them.
And yet, there is hope! Jesus continued, “. . . but for the elect’s sake those days will be shortened.” In the absence of a loving Creator, the collective sins of mankind would be our undoing—but God, out of mercy and love for His people, will intervene before AI or any other threat would destroy mankind.
Until the return of Jesus Christ, the world we live in will become increasingly dangerous and unpredictable. Paul warned that “in the last days perilous times will come” (2 Timothy 3:1). AI advances are worsening many spiritual dangers. Social media will become more addictive and more toxic. Advertising will become more enticing than ever, fueling hedonism. Deceptive AI content will soon make it nearly impossible to tell truth from reality. All these problems and more are at our doorstep!
What should we do as AI races ahead? Stay spiritually awake, testing every claim against God’s Word, and remember that the only true hope for the world is the coming Kingdom of God.
Our world is charging toward a future it cannot control—but, thankfully, that future is securely in the hands of God the Father and Jesus Christ. For our sake, man’s self-destructive course will be cut short, and God’s Kingdom will bring the peace that no human-devised AI could ever deliver!
****
LOLGB+
#agi #AI #artificialIntelligence #chatgpt #technology -
Some fiery speeches yesterday evening at an emergency gathering in Nottingham, England, to protest the recent Israeli incursions into Hebron. 60-odd of us was an impressive turnout on a weekday evening at such short notice.
Sadly my sore throat prevented me from contributing a speech (I was asked), but that's me bottom right in the second pic.
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The Best Travel Advice I Follow Was Never Given to Me
Lessons learned from years of wandering, getting lost, and finding myself along the way.I can’t remember exactly when traveling became such an important part of my life. Perhaps it happened gradually, somewhere between the responsibilities of raising a family, building a career, and trying to find a little space for myself in a life that always seemed to demand so much of me.
I didn’t grow up imagining that one day I would be wandering through unfamiliar cities, sitting alone in cafés thousands of miles from home, or watching sunsets in places I had only seen in photographs.
But somehow, life brought me there.
I’ve walked through the streets of European towns, admired ancient temples, wandered around bustling Asian cities, and found myself sitting quietly by the sea, doing absolutely nothing except enjoying the moment.
Some journeys were carefully planned. Others came with unexpected turns. There were moments of excitement, confusion, exhaustion, and occasionally, a little fear.
And speaking of fear, my recent trip to Ba Na Hills in Da Nang, Vietnam, gave me one of those moments when I seriously questioned my own travel decisions.
There I was, alone inside a cable car, making my way up the mountains. The scenery was breathtaking, but being suspended so high above the ground, with nobody else inside the cabin, was another experience altogether.
I tried to appreciate the magnificent view, but somewhere along the way, a thought crossed my mind:
Was choosing to travel alone really a good idea?
Of all the places where I could question my independence, it had to be inside a cable car, high above the mountains!
And just when I thought I had conquered that little moment of fear, I remembered that I still had to take the cable car going down.
Another round of courage required!
But I made it, of course.
And looking back, I can laugh about it now. Because that’s the thing about solo traveling. Sometimes you feel incredibly brave and independent, and other times you find yourself silently questioning your life choices while hanging somewhere above the treetops.
Yet, despite those moments, I wouldn’t trade the experience.
Later, during that same trip, I found myself at My Khe Beach, looking at the beautiful blue sky and the sea. There was something about the way they seemed to meet, almost as though they were holding each other, that gave me an extraordinary sense of peace.
I wasn’t thinking about where I needed to go next or what else I should see before leaving Vietnam.
For once, I was perfectly content just being there.
It struck me how one journey could give me two completely different feelings: a little fear high above the mountains and an overwhelming sense of calm beside the sea.
And perhaps that is exactly what traveling has been teaching me all these years.
That I can be afraid and still be adventurous.
That I can enjoy my own company without necessarily feeling lonely.
That not every experience has to be comfortable to become a beautiful memory.
I’ve never really had a particular set of travel rules. I don’t remember anyone sitting me down and giving me advice about how to become a good traveler.
Most of what I know, I learned by going places, making decisions, getting things wrong occasionally, laughing at myself, and discovering what truly matters to me.
And if I were asked today what piece of travel advice I follow, I think my answer would be surprisingly simple:
Travel at your own pace. Trust your instincts. And never be too busy exploring a place that you forget to experience it.
After all, sometimes traveling teaches us to appreciate the view.
And sometimes, it teaches us that we’re a little braver than we thought, even when we’re quietly wishing there were someone else inside that cable car! 😂
Not Every Journey Needs a Perfect Itinerary
I used to think that making the most of a trip meant visiting as many attractions as possible.
After all, traveling costs money, time, and effort. Naturally, we want to make every moment count.
But over the years, I’ve learned that the most memorable experiences aren’t necessarily the ones written on my itinerary.
Sometimes, it’s a quiet café tucked away on an unfamiliar street.
Sometimes, it’s an old church that I discover while walking around a city.
Sometimes, it’s watching the sunset, listening to the waves, or enjoying a cup of coffee while the world carries on around me.
I’ve learned that I don’t need to rush from one attraction to another just to say I’ve been there.
Some places deserve more than a quick photograph.
They deserve my time and attention.
It’s Okay to Travel Alone
Solo traveling has taught me many things about myself.
I’ve learned to navigate unfamiliar places, make decisions independently, communicate despite language barriers, and find my way when things don’t go exactly as planned.
But perhaps the most important thing I’ve learned is that being alone doesn’t necessarily mean being lonely.
There is a certain freedom in waking up without having to consider anyone else’s schedule.
I can spend an entire morning in a café, walk along the beach, visit a church, or change my plans simply because I feel like doing something different.
I don’t have to explain why I want to stay longer or why I prefer a quiet place over a crowded attraction.
And somehow, in those moments of solitude, I feel more connected to myself.
Listen to What a Place Makes You Feel
During my recent trip to Da Nang, Vietnam, I experienced something difficult to explain.
There was something about the city that made me feel peaceful.
Perhaps it was the blue sky meeting the sea at My Khe Beach, the mountains surrounding the city, or the unhurried atmosphere that allowed me to breathe a little easier.
I had visited beautiful places before, but Da Nang gave me a different feeling.
I felt at home.
That experience reminded me that sometimes, the best destinations aren’t necessarily the most famous or expensive ones.
They are the places that make us feel something we didn’t even know we needed.
Leave Room for the Unexpected
Traveling has also taught me to be flexible.
Not everything will go according to plan.
There will be delays, changes in weather, unfamiliar food, language barriers, and occasional disappointments.
But I’ve learned not to allow small inconveniences to ruin an entire journey.
Some of my favorite travel memories came from moments I never planned.
A beautiful view along the road.
An unexpectedly good cup of coffee.
A conversation with a stranger.
Or a place that wasn’t even on my list.
Sometimes, the detour becomes the highlight of the trip.
Travel for Yourself, Not for Validation
In a world where every destination seems to be measured by how beautiful it looks on social media, it’s easy to feel that we need to visit popular places, take perfect photographs, and share every experience.
I enjoy taking photographs and sharing my travels, too.
They are part of how I preserve memories and tell stories.
But I’ve learned that not every beautiful moment needs to be documented.
Some memories are meant to be experienced quietly.
Some sunsets are meant to be watched without reaching for a phone.
And some of the most meaningful experiences are the ones that no photograph can fully capture.
I travel because I enjoy discovering places, learning about different cultures, and experiencing life beyond the familiar.
Not because I need to prove that I’ve been somewhere.
The Advice I Didn’t Know I Was Following
Now, if someone asks me what travel advice I follow, I think I finally know my answer.
Don’t travel just to see places. Travel to experience them.
Take photographs, but don’t forget to look around.
Make plans, but allow yourself to change them.
Visit famous landmarks, but appreciate the quiet corners.
Be adventurous, but listen to your instincts.
And most importantly, don’t feel guilty about slowing down.
I have spent much of my life taking care of responsibilities, meeting expectations, and making sure the people who matter to me are okay.
Traveling has taught me that I also deserve moments that belong entirely to me.
Moments when I don’t have to be responsible for everything.
Moments when I can simply enjoy being alive.
Perhaps that’s why certain places leave such a lasting impression on me.
They remind me that life is not only about what we accomplish or how much we can carry.
It is also about what we allow ourselves to experience along the way.
And if there’s one piece of travel advice I would pass on to someone else, it would be this:
Go somewhere that makes you curious. Stay long enough to feel something. And return home with more than photographs.
Return with memories, perspective, gratitude, and perhaps a little more understanding of yourself.
Because sometimes, the most beautiful thing we discover while traveling isn’t the destination.
It’s the version of ourselves we find when we finally have the freedom to slow down.
And occasionally, it’s discovering that we can survive a cable car ride alone, even when our courage briefly decides to take a holiday of its own. 😂
Jhie Beyond Borders | Travel, Life & Reflections
#SoloTravel #TravelReflections #JhieBeyondBorders #TravelAtYourOwnPace #SlowTravels
#dailyprompt #dailyprompt2927 #discovery #journey #soloTravel #travel #wanderlust -
#Writephant 2026.1026 — A4 It's almost November! What writing/publishing goals do you plan to focus on for the rest of the year?
If I could reconnect, 20K words would serve to finish Reluctant Courier. That's a month's work. If not, revise Mars Needed Women with beta reader edits, or rewrite to 1st person Through Blood and Tears.
[Author retains copyright (c)2026 R.S.]
#gender #fiction #writer #author
#writing #writingcommunity #writersOfMastodon #writers
#RSdiscussion -
The Meteorological Musings Of A Rather Decaying And Incoherent Mind;
According to looking at the sky and the squirrels, there is a massive amount of moisture getting pulled from the gulf moving North West, and it appears that it is going to mix with a massive cold front coming down from the Northwest going south east, I'd say somewhere within the next 72 hours there is going to be a massive snow storm moving across the Rockies and dropping temperatures across the plains the South the Midwest and all the way into New England with widespread snow and rain throughout the country, don't take my word for it look at the sky and watch the squirrels;
You can encourage my continued useless #poetry, creativity and expression of self, #commentary, random thoughts, #philosophy and ideas, and by doing so your helping to feed, house and clothe a #disabled man living in #poverty, $5-10-15 It All Helps, via #cashapp at $woctxphotog or via #paypal at paypal.com/donate?campaign_id=…
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@DjityDjity
Yes, there is rage. And most people feel so disempowered and disconnected from politics that they have no *safe outlets* for their rage, and so…I agree with the violence our kids are dealing with everyday because of the *toxic elements* they get exposed to *online* but also from *peers*. The *manosphere* is a real thing and a pest on society. Eradication of this pest starts in *preschool* and relentlessly throughout a person’s education (there ought to be compulsory *civic lectures* at Uni level to fight this scourge imo. But, above all, we need to see civility from our political leaders because *leadership* demands role modeling and examples always come **From the top down.**
#Civility #CivicLeadership #AUsPol #Violence #NormativeViolence #ElectorateRage #Femicide #DeathsInCustody #OfficialViolence #PoliticalRepression #SkewedLegalSystems #ClassWarfare #WealthInequity #InadequateSocialServices #MentalHealthCare I could add more hashtags…
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«Democracy has proven unable to reign in capitalism. China executes or life imprisons billionaires who break the law, we bail them out and immunize them from their crimes by fining their companies, but not them, leaving them still rich.
It all adds up to a horrid indictment of our system, and people are not going to put up with it forever. Liberal capitalism and liberal democracy, and perhaps democracy almost entirely, will be replaced by Party systems throughout the world over the next couple generations, starting, I’d guess, in about 15 years or so.
Failure, greed and incompetence have consequences, and the [sic] democracy will [be] one of the casualties of our elites depravity.»
As someone in my 60s, who was able to, without especially great effort on my part, do reasonably well in my life, it is still shocking to encounter sentiments like this. But I've been reading Welsh's articles for probably a year or more now, and I find I can't dismiss his basic arguments. Will the "death of democracy" come to pass? I don't know and neither does Welsh, but the rise of extreme inequality, the consequent capture of our institutions and governments by the wealthy few, and the collapse of opportunity for those foolish enough not be born when those things were at least less true cannot bode well for our political institutions.
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My first paper went well today. Unlike my classmates, my professor was literally like "I don't have any notes to give you beyond small grammar I'm not too concerned about, you did a good job" and then started telling me specific things he really liked like the amount of detailed examples I gave.
I finished writing the paper, with his approval over the final two paragraphs, by like halfway through class and just kind of sat around making finicky edits to kill time while he helped the other two students who were still working on their papers.
2/2 -
Say is *loud and clear* Amy. Good Golly I just love me a few #AmyRemeikis slaps in the face of reality thinking. She does *Journalism* proud with every article. And this one hits the nail on the head again. Every time I read Amy, I feel like I know her.
## Politicians telling us to ‘turn the temperature down’ is peak hypocrisy – Amy Remeikis
> Violence is being normalised in Australia, and legitimate democratic dissent is not the fire – it’s the alarm
> “On the broader question of violence, we are a state and society that increasingly normalises violence. We’ve normalised a man killing a woman each week. We’ve normalised police bashing peaceful protesters. We’ve normalised throwing First Nations kids in jail until they kill themselves. We’ve normalised shackling women in labour. We’ve normalised delaying climate action even as we see the devastating impacts, and we’ve normalised an economy that prioritises corporate profits while people suffer.”
And that alarm has been ringing for some years now imo.
https://www.deepcutnews.com/p/politicians-telling-us-to-turn-down#AusPol #Violence #PoliticalMachinations #Society #NormativeViolence
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One of my favorite shit post videos probably got copyright claimed. It's the old ECW theme song playing against a cheesey work place safety video as various actors do incredibly unsafe things to teach potential employees about safety... so I'm recreating it from memory and grabbing other safety videos from various eras.
Why it's funny if you're under 40 and not getting it - this was the theme song the accidents were set to
https://www.youtube.com/watch?v=2kNxmxT3Wnw
(warning you'll see humans tossed around or thrown into barbed wire and other violence) -
#Exmoor - Beyond the Stars - an interactive evening at #QuinceHoneyFarm
28 October 2026 / 6:00pm - 9:00pm
Quince Honey Farm, Aller Cross, #SouthMolton EX36 3RD"Discover the wonders of the universe at our interactive space event as part of the Exmoor Dark Skies Festival 2026, with Jo and Pete from Spaces Detectives and Kate Earl from Skyhigh Astronomy, and featuring various immersive activities!
A talk and presentation will firstly set the space scene, before being taken on a journey through the stars as you enter the #planetarium dome, then leave Earth behind as you use VR Showtime headsets to go on a virtual voyage into space.
Lastly, if the skies are clear, you are invited to #StarGaze from our #NectarGardens using high end “Go To” telescopes, with #astronomers on hand to guide and assist. As well as all of this, you can take a browse of the #astrophotography gallery with opportunity to speak with astronomers. It is set to be a packed, unforgettable experience guaranteed to leave you in awe!
To fuel your journey into space you will begin the evening with a seasonal warming supper [details at link below]. Please note, the menu will utilise fresh and homegrown produce from our Kitchen Garden and therefore may vary slightly from what is listed above. Both of these options can be offered gluten free and dairy free."
Time: 6:30pm – 9pm (doors open at 6pm, finish time is approx)
Ticket Price: £32.50
FMI and to make reservations:
https://www.exmoor-nationalpark.gov.uk/exmoor-for-everyone/stargazing-and-dark-skies/exmoor-dark-skies-festival/dark-sky-festival-events/dsf-events-26/beyond-the-stars-an-interactive-evening-at-quince-honey-farm#LunarPunkMonday #ExmoorDarkSkiesFestival #Planetarium #StarGazing #SpendTimeOutdoors #LearnAboutTheStars #DarkSkiesFestival #UKEvents
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#SanFrancisco #BallotMeasures #MoreCityHallBS #snailmail #propaganda
"Orwellian arguments, fuzzy math and a hippie cult: This is the dawning of the S.F. midterm electionMayor Lurie’s arguments have grown Orwellian and his math isn’t mathing. But it’s hard to foresee voters denying him anything he asks for.
Like you, I was surprised when a political advertisement depicting nine berobed, hairy people (and a cat) was crammed through my mail slot. 'No one knows better than SF,' the mailer read, 'Communes just don’t work.' It then exhorted us to vote 'Yes' on Prop. C and 'No' on Prop I in the November election.
Sorry, what? If this is a Jonestown reference, the 'commune' part of that arrangement was the least of everyone’s worries. What does a group of people who look like the second-run traveling cast of 'Jesus Christ Superstar' have to do with the midterm elections? The Prince of Peace, after all, could spring for 12 apostles, not eight.
(. . .)
That 'right to participate directly and meaningfully,' it seems, is the 'commune' the flyer is warning of — though it also sounds kind of like a suburban HOA or the board elections for your average condo complex. By this measure, the Freedom West co-op, whose redevelopment plan was last week lauded by Prop. I foe Mayor Daniel Lurie, is also a 'commune,' albeit one primarily inhabited by African American seniors and families, not weird hippies with a salad empire."
https://missionlocal.org/2026/10/daniel-lurie-san-francisco-elections/
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A fearless breakdown of Title IX's gutting, Trump's plummeting polls, Palau's climate plea, and six new LGBTQ+ victories—finding resistance and hope where power fails our kids. #Trans #TransRights #LGBTQ #QueerNews #Politics #News #Journalism #HumanRights #Resist #Solidarity #Democracy https://thistleandmoss.com/p/fixed-it-for-you-you-orange-thundercunt-title-ix-gutted-the-polls-through-the-floor-and-palau-just-w
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Ah, the GPT-6.1 Terra 🎩—where you can explore the labyrinth of #markdown files and #APIs while pretending you're in the #Matrix. 🤖 Just remember, the true challenge is not in mastering the AI’s capabilities, but in staying awake through the documentation. 💤
https://developers.openai.com/api/docs/models/gpt-6.1-terra #GPT6.1Terra #AI #Challenges #HackerNews #ngated -
It’s getting hot in here – a Perimenopause evening by Bustie La Tish
De Nieuwe Anita, Wednesday, December 9 at 08:00 PM GMT+1
Start: 20.00. Tickets: 15,-
It’s getting hot in here – a Perimenopause evening by Bustie La Tish
Join Bustie La Tish for an evening of laughter, learning and letting go through storytelling, burlesque and comedy around (peri-)menopause.
Life was a bed of roses for burlesque star Bustie La Tish, until she discovered that the sneaky symptoms spoiling her best life were caused by perimenopause. In this burlesque storytelling performance, Bustie shares her educational and hilarious journey with Dutch doctors, self-help books, period underwear, and more.
Expect audience interaction, hilarious stories, sexy performances but also lots of sharing and learning to break this taboo!
Whether you are going through ‘the change’ yourself or educating yourself on what’s to come for you or your loved ones, you will come out of this evening more informed and comforted.
Bustie La Tish is a French performance artist based in Amsterdam, whose work spans performance art, burlesque, storytelling, and comedy. Bustie brings fearless authenticity to every stage — exploring themes of vulnerability, sensuality, desire, and body liberation with humour, warmth, and unapologetic sass. Beyond performing, Bustie creates shows like GOSH! (A Good Old Sexy Happening!) and Smut Slam Amsterdam (sex-positive storytelling), weaving activism and artistry into joyful events.
https://offbeat.amsterdam/event/its-getting-hot-in-here-a-perimenopause-evening-by-bustie-la-tish