#prediction — Public Fediverse posts

Radiation trends conduct to revising climate predictions upward.

"Recent data of the amount of heat energy trapped within the Earth system—the energy imbalance—indicates that Earth may actually be warming faster, aligned with models that forecast higher temperatures."

"Our findings indicate that it becomes increasingly difficult to exclude models with strong future warming."

Gyuleva, G., Fischer, E., Knutti, R., & Sippel, S. (2026). "Recent temperature and energy imbalance trends point to higher estimates of future warming" https://doi.org/10.1029/2026EF008356

#anticipation #future #futures #projections #forecast #prediction #climate #climateCollapse #climateChange #globalHeating #globalWarming #climateCrisis #science

#ApeXProtocol is now trending across Mastodon

#Top5DEX is now trending across Mastodon

#ApeX is now trending across Mastodon

#Prediction is now trending across Mastodon

#みんなのキャラデザ見せて is now trending across Mastodon

#Prediction This years hottest Halloween costume: Flock Shearer

Ngrok's blog attempts to convince us that "compression is prediction" while simultaneously squeezing out more #buzzwords than a #Silicon #Valley startup pitch 🏢🔮. If you manage to navigate the labyrinth of tech jargon and promises of making AI smaller, faster, and cheaper, congratulations—you've just wasted time you'll never get back 🤦‍♂️.
https://ngrok.com/blog/compression-is-prediction #Ngrok #Compression #Prediction #TechJargon #HackerNews #ngated

Compression Is Prediction

https://ngrok.com/blog/compression-is-prediction

Comments: https://news.ycombinator.com/item?id=49263497

#HackerNews #Compression #Prediction #DataScience #Technology #Insights

#Shrike26 Hypercube Election #Prediction

August Senate updates:
GA-Sen to 🟦 Safe D (was Likely D)
NE-Sen to 🔸 Lean I (was Tilt I)

ME-Sen to 🔹 Lean D (was Likely D)
NH-Sen to 🔵 Likely D (was Safe D)
MT-Sen to 🟥 Safe R (was Likely R)
FL-Sen to 🔴 Likely R (was Tilt R)
IA-Sen to ♦️ Lean R (was Tilt R)

"The original URL for this prediction will no longer be available in 11 years." (2011)

https://longbets.org/601/

Comments: https://news.ycombinator.com/item?id=49228458

#HackerNews #originalURL #prediction #longbets #futuretech #11years

Apparently they could do math in 1912.

#ClimateChange #prediction

Did a 1912 Newspaper Article Predict Global Warming? | Snopes.com
https://www.snopes.com/fact-check/1912-article-global-warming/

🌪️ Oh joy, DeepMind's new #AI can now predict cyclones, because apparently, weather forecasters with decades of experience weren't doing it justice. 🤖🌀 But don't worry, it's all part of Google's master plan to create a dystopian weather channel where robots explain why your vacation was ruined. 💨😂
https://deepmind.google/blog/weathernext-ai-model-achieves-breakthrough-in-forecasting-cyclones/ #DeepMind #Cyclone #Prediction #WeatherTech #DystopianFuture #HackerNews #ngated

[Open] Data Related To Flood Mapping [Canada]
--
https://natural-resources.canada.ca/science-data/science-research/natural-hazards/flood-mapping/data-related-flood-mapping <-- shared link to technical details
--
https://app.geo.ca/en-ca/map-browser/record/a13a2575-5bda-4bfd-a9b1-5bd2dd583f09 <-- shared map/data-portal link, Canada Flood Map Inventory (CFM)
--
https://open.canada.ca/data/en/dataset/1074f781-85d3-4c86-86cb-fd1c339197dc <-- shared data-portal link, Canada Flood Susceptibility Index
--
https://doi.org/10.3390/ECWS-7-14235 <-- shared (2023) paper
--
https://doi.org/10.1002/2017WR020917 <-- shared (2017) paper
--
H/T @Michael DePue | VP & AtkinsRéalis Fellow for Water Resources Engineering | PE, PMP, CFM
“At the Canadian Water Resources Association National Conference in Winnipeg, colleagues shared insights from Canada's Flood Hazard Identification and Mapping Program. This initiative has seen over 400 flood mapping projects and more than 1,000 flood hazard maps produced, supported by a substantial investment of $164.2 million from 2024 to 2028.
Two key datasets:
• The Canada Flood Map Inventory, which records the locations of flood hazard maps and provides information on how to access them.
• The national Flood Susceptibility Index, a machine-learning assessment of flood-prone areas, including regions that have not been mapped in detail.
When these two layers are combined on a single screen, it becomes clear where future mapping efforts should be directed — specifically, areas with high susceptibility that currently lack detailed maps…”
#water #hydrography #flood #flooding #risk #hazard #model #modeling #fedscience #publicsafety #humaninpacts #opendata #Canada #GIS #spatial #mapping #damage #infrastructure #floodmapping #prediction #spatialanalysis #spatiotemporal #historic #current #future #preduction #extremeweather #metrology #rainfall #precipitation #atmosphericriver #FloodMapInventory #CFM #floodhazard #FloodSusceptibilityIndex #floodprone #research #susceptibility
@NRCAN

Minority Report for Real pt2 --- Minority Report: FBI Seeks AI for Political Watch List
Documents show the FBI seeking AI tools to flag Americans before they act, as the terror watch list's focus moves toward domestic dissent. [ Threat Screening Center (TSC)]

https://reason.com/2026/07/28/minority-report-fbi-seeks-ai-for-political-watch-list/

#AI #Crime #Datamine #facist #FBI #intelligence #Mine #MinorityReport #Prediction #Politics #Surveillance #tech #technology #terrorism #threat #Trump #TSC #watchlist #ThreatScreeningCenter
#TerroristScreeningCenter #antifa

Minority Report -- Trump Pre-Crime AI Plan Would Mine Ordinary Citizen Data To Flag Threats Before Any Crime Is Committed
The bureau already buys Americans' location data from brokers, its own director has told Congress

https://www.ibtimes.co.uk/fbi-ai-system-predict-domestic-threats-1811452

#AI #Crime #Datamine #FBI #Mine #MinorityReport #Prediction #Politics #tech #technology #threat #Trump

Theo Conjecture solves 35-year-old math problem, finds a term no one predicted

https://firstprinciples.com/blog-article/ai-system-theo-conjecture-solves-35-year-old-math-conjecture

Comments: https://news.ycombinator.com/item?id=49102525

#HackerNews #TheoConjecture #MathProblem #Breakthrough #AIResearch #Prediction

The Great AI Job Replacement Continues to Fail to Materialize

The theory that AI will replace everyone at work is looking worse and worse and a new report strikes another blow to that theory.

https://www.freezenet.ca/the-great-ai-job-replacement-continues-to-fail-to-materialize/

#News #Technology #2026 #AI #employment #journalism #prediction

@jeffjarvis
2/
The Guessing Engines Compared
The Mechanism:

LLM: Autoregressive prediction operating over high-dimensional vector spaces. It guesses the statistically most probable next token.

Human Brain: Hierarchical Bayesian inference operating over sensory inputs, motor feedback, and internal state signals. It guesses the next physical and internal state.

#LLM
#brain
#prediction

When Prediction Becomes a Social Logic: How AI Is Reshaping How We Imagine the Future

Stay curious — follow @1ban_news.

https://1ban.news/ai-warping-social-fabric-prediction/

#1ban #warping #social #fabric #prediction #science

Noobeer Prophecy: FIFA World Cup 2026

The biggest stage in football awaits tomorrow, Sunday, July 19, 2026, as defending champions Argentina face European powerhouse Spain in the World Cup Final at MetLife Stadium in New York/New Jersey.

Staying true to the Noobeer Prophecy — pure gut instinct, zero stats, no tactical breakdowns, no betting lines — just raw vibes. The latest accuracy update is here.

For the grand finale, my intuition is locked in:

• Argentina will defeat Spain
Spain plays beautiful, technical football and arrives in red-hot form, but something about Argentina’s champion mentality, experience in these moments, and that never-say-die spirit (with Messi still leading the charge) feels destined to prevail. The gut says the Albiceleste etch their names in history with back-to-back World Cups.

No deep analysis — just the vibe. That’s the entire beauty of the prophecy: testing raw human intuition against the magic and chaos of the world’s biggest sporting event.

Will Argentina deliver and boost the accuracy, or will Spain write a new chapter in glory? Tune in tomorrow (3 PM ET on FOX) and let’s find out together.

Enjoy the final! ⚽🏆

"Yes, how can I #help you?" Natalia continued the conversation patiently, although she was growing #irritated . She knew what would be said next.

"Isn't there a male #mechanic the man asked, confirming her #prediction .

almost, but not

almost, but not 
everything is 
rigged, so we tell 
ourselves as we fold 
up the new york 
times’s athletic 
section for the 
third and final 
time, knowing that 
the winner is always 
the one that drives 
the predictions, 
watching, waiting
.
20260715:1840
y

Foundation models and earth embeddings: Konstantin Klemmer et al.’s #ISPRS 2026 tutorial on #FoundationModels and #EarthEmbeddings pairs free, MIT-licensed slides with hands-on Colab notebooks spanning four practical use cases, from direct #prediction to geo-#semanticSearch. Kiri...
https://spatialists.ch/posts/2026/07/15-foundation-models-and-earth-embeddings/ #GIS #GISchat #geospatial #SwissGIS

Mapping Deforestation Probability And Understanding The Forest Dynamics In Gazipur, Bangladesh
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https://doi.org/10.1016/j.envc.2026.101568 <-- shared paper
--
"ABSTRACT: Deforestation is a spiralling environmental catastrophe with impervious results for biodiversity, climate change, and human livelihoods, specifically in tropical regions. Being a tropical country, Bangladesh has experienced approximately 40% loss of its forest cover, at Gazipur since 1930, which contains about 86% of the country's Sal (Shorea robusta) forest, ranging approximately 4,300 hectares per year (2001–2010) to over 19,500 hectares per year (2011–2020), exemplifying an intensification of nearly 353%. The objective of this study is to map deforestation probability at the Gazipur district of Dhaka Division, Bangladesh, by utilising machine learning algorithms along with multi-source geospatial data, with the purpose of identifying high-risk zones and facilitating evidence-based forest governance, land-use development, and prioritizing conservation areas. This study integrated twelve conditioning factors, including biophysical, landscape, and anthropogenic. To identify susceptible zones the study trained and assessed five machine learning algorithms; RF, XGBoost, ANN, NB, and MLP and validating the result through different metrics like sensitivity, specificity, precision, accuracy, F1-score, AUC. The performance of the models was evaluated using Wilcoxon signed-rank tests and marginal response curves (MRC) were used to understand factor contributions. In the result, RF achieved highest performance with accuracy of 84% and AUC of 0.93, followed by XGBoost at 83% accuracy and 0.92 AUC. Rainfall and population density were most dominant conditioning factors among models. Pairwise statistical testing resulted that ensemble-based algorithms (RF, XGBoost) generated statistically comparable and significantly higher predictions compared to NB and MLP. Spatial probability maps indicate areas of high and very high risk in the south-western and north-eastern upazilas. The results can be applicable for forest management authorities, urban planners, and policymakers, and correspond with SDG Indicator 15. An inclusive governance framework containing land zoning, ecological area identification, and compliance with industrial EIA is proposed to persuade probability maps into adaptive forest management strategies…”
#deforestation #probability #machinelearning #algorithms #AI #Gazipur #Bangladesh #GIS #spatial #mapping #spatialanalysis #spatiotemporal #rainfall #precipitation #humanimpacts #populationpressure #risk #prediction #RandomForest #conservation #restoration #environment #biodiversity, #climatechange #human #livelihood #tropical #forestcover #sal #forest #vegetation #tree #upazila #spatialprobability #geostatistics #forestmanagement #planning #policy #urbanplanners #governance #zoning #ecology #habitat

Rejourney – Open-source revenue leak prediction for web and mobile apps

https://github.com/rejourneyco/rejourney

Comments: https://news.ycombinator.com/item?id=48904912

#HackerNews #Rejourney #OpenSource #RevenueLeak #Prediction #WebApps #MobileApps

#Prediction ? #Vibe_engineering