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✮ Anatomy of Brokenness ✮

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Time to pause, reflect, and just be grateful. 🌙✨
Now, it's time to disconnect, recharge, and get ready for a fresh start tomorrow.

Goodnight, everyone! Sleep well. 💤🛌🌏

#GoodNight #Rest #Gratitude #PeacefulMind #Recharge

Time to pause, reflect, and just be grateful. 🌙✨
Now, it's time to disconnect, recharge, and get ready for a fresh start tomorrow.

Goodnight, everyone! Sleep well. 💤🛌🌏

#GoodNight #Rest #Gratitude #PeacefulMind #Recharge

🎉 New Blog Post: Sane API error handling with RFC 9457 Problem Details in Java https://mehmandarov.com/rfc-9457-problem-details-jakarta-ee/

#jakartaee #java #rfc9457 #api #rest

🎉 New Blog Post: Sane API error handling with RFC 9457 Problem Details in Java https://mehmandarov.com/rfc-9457-problem-details-jakarta-ee/

#jakartaee #java #rfc9457 #api #rest

🎉 New Blog Post: Sane API error handling with RFC 9457 Problem Details in Java https://mehmandarov.com/rfc-9457-problem-details-jakarta-ee/

#jakartaee #java #rfc9457 #api #rest

🎉 New Blog Post: Sane API error handling with RFC 9457 Problem Details in Java https://mehmandarov.com/rfc-9457-problem-details-jakarta-ee/

#jakartaee #java #rfc9457 #api #rest

🎉 New Blog Post: Sane API error handling with RFC 9457 Problem Details in Java https://mehmandarov.com/rfc-9457-problem-details-jakarta-ee/

#jakartaee #java #rfc9457 #api #rest

Laying high

#elevated #rest

Laying high

#elevated #rest

https://www.fogolf.com/1267656/danny-lee-dropped-by-liv-golf-team-for-rest-of-season/ Danny Lee dropped by LIV Golf team for rest of season #After #being #by #Called #Club #DANNY #Dropped #for #formerly #Golf #GolfNews #golfer #ironheads #Kiwi #korean #Lee #Liv #of #remainder #Rest #Season #Team #WILDCARD #will

https://www.fogolf.com/1267656/danny-lee-dropped-by-liv-golf-team-for-rest-of-season/ Danny Lee dropped by LIV Golf team for rest of season #After #being #by #Called #Club #DANNY #Dropped #for #formerly #Golf #GolfNews #golfer #ironheads #Kiwi #korean #Lee #Liv #of #remainder #Rest #Season #Team #WILDCARD #will

Men resting together at midday, China, 1920s

https://piefed.social/c/historyphotos/p/2088304/men-resting-together-at-midday-china-1920s

Men resting together at midday, China, 1920s

https://piefed.social/c/historyphotos/p/2088304/men-resting-together-at-midday-china-1920s

Men resting together at midday, China, 1920s

https://piefed.social/c/historyphotos/p/2088304/men-resting-together-at-midday-china-1920s

Men resting together at midday, China, 1920s

https://piefed.social/c/historyphotos/p/2088304/men-resting-together-at-midday-china-1920s

Men resting together at midday, China, 1920s

https://piefed.social/c/historyphotos/p/2088304/men-resting-together-at-midday-china-1920s

The day is officially done, and it is time to put down the heavy glass of today's worries. 🌊✨

No matter what you didn't finish, what stressed you out, or how hard the grind was, give your brain and body permission to fully rest tonight. Tomorrow is a brand new page with brand new energy.

Goodnight, Fediverse. Sleep well and wake up refreshed! 🌌🛌💤

#GoodNight #BedtimeThoughts #Rest #ProtectYourPeace #Fediverse

The day is officially done, and it is time to put down the heavy glass of today's worries. 🌊✨

No matter what you didn't finish, what stressed you out, or how hard the grind was, give your brain and body permission to fully rest tonight. Tomorrow is a brand new page with brand new energy.

Goodnight, Fediverse. Sleep well and wake up refreshed! 🌌🛌💤

#GoodNight #BedtimeThoughts #Rest #ProtectYourPeace #Fediverse

RT @ChujieZheng: For Qwen3.7-Max, we have invested far more compute into RL training than ever before. Its top-tier AA score confirms the resulting general and agentic capabilities. This is just the start. We will firmly push forward RL scaling to build more powerful Qwen models. Stay tuned! Artificial Analysis (@ArtificialAnlys) Alibaba’s new Qwen3.7 Max model scores 56.6 on the Artificial Analysis Intelligence Index, 4.8 points higher than Qwen3.6 Max Preview (51.8). While Alibaba still trails models from OpenAI, Anthropic and Google, Qwen3.7 Max is the closest they have been to the frontier Qwen3.7 Max is @Alibaba_Qwen's latest proprietary flagship, scoring 56.6 on the Intelligence Index, a 4.8 point gain over Qwen3.6 Max Preview (51.8) released in April. Qwen3.7 Max continues Alibaba's pattern, in place since Qwen2.5 Max (January 2025), of releasing Max and Plus models as closed weights while the rest of the Qwen line remains open weights. The leading open weights Qwen on the Intelligence Index is Qwen3.6 27B (Reasoning, 45.8) released in April 2026, and the leading open weights MoE Qwen is Qwen3.5 397B A17B (Reasoning, 45.0) released in February 2026 Key takeaways for the reasoning variant: ➤ The Intelligence Index gains over Qwen3.6 Max Preview are concentrated in scientific reasoning, agentic capability and coding. CritPt +9.7 p.p (3.7% to 13.4%), HLE +9.2 p.p (28.9% to 38.1%), TerminalBench Hard +6.9 p.p (43.9% to 50.8%) and GDPval-AA +42 Elo (1504 to 1546). Scores on other benchmarks in the Intelligence Index are flat compared to Qwen3.6 Max Preview ➤ A significant share of the Int…

mehr auf Arint.info

#Alibaba #Anthropic #API #Claude #DeepSeek #Gemini #Google #GPT5 #nitter #OpenAI #Qwen #Qwen25 #Qwen35 #Qwen36 #Qwen37 #rest #arint_info

https://x.com/ChujieZheng/status/2057403166589956518#m

RT @ChujieZheng: For Qwen3.7-Max, we have invested far more compute into RL training than ever before. Its top-tier AA score confirms the resulting general and agentic capabilities. This is just the start. We will firmly push forward RL scaling to build more powerful Qwen models. Stay tuned! Artificial Analysis (@ArtificialAnlys) Alibaba’s new Qwen3.7 Max model scores 56.6 on the Artificial Analysis Intelligence Index, 4.8 points higher than Qwen3.6 Max Preview (51.8). While Alibaba still trails models from OpenAI, Anthropic and Google, Qwen3.7 Max is the closest they have been to the frontier Qwen3.7 Max is @Alibaba_Qwen's latest proprietary flagship, scoring 56.6 on the Intelligence Index, a 4.8 point gain over Qwen3.6 Max Preview (51.8) released in April. Qwen3.7 Max continues Alibaba's pattern, in place since Qwen2.5 Max (January 2025), of releasing Max and Plus models as closed weights while the rest of the Qwen line remains open weights. The leading open weights Qwen on the Intelligence Index is Qwen3.6 27B (Reasoning, 45.8) released in April 2026, and the leading open weights MoE Qwen is Qwen3.5 397B A17B (Reasoning, 45.0) released in February 2026 Key takeaways for the reasoning variant: ➤ The Intelligence Index gains over Qwen3.6 Max Preview are concentrated in scientific reasoning, agentic capability and coding. CritPt +9.7 p.p (3.7% to 13.4%), HLE +9.2 p.p (28.9% to 38.1%), TerminalBench Hard +6.9 p.p (43.9% to 50.8%) and GDPval-AA +42 Elo (1504 to 1546). Scores on other benchmarks in the Intelligence Index are flat compared to Qwen3.6 Max Preview ➤ A significant share of the Int…

mehr auf Arint.info

#Alibaba #Anthropic #API #Claude #DeepSeek #Gemini #Google #GPT5 #nitter #OpenAI #Qwen #Qwen25 #Qwen35 #Qwen36 #Qwen37 #rest #arint_info

https://x.com/ChujieZheng/status/2057403166589956518#m

RT @ChujieZheng: For Qwen3.7-Max, we have invested far more compute into RL training than ever before. Its top-tier AA score confirms the resulting general and agentic capabilities. This is just the start. We will firmly push forward RL scaling to build more powerful Qwen models. Stay tuned! Artificial Analysis (@ArtificialAnlys) Alibaba’s new Qwen3.7 Max model scores 56.6 on the Artificial Analysis Intelligence Index, 4.8 points higher than Qwen3.6 Max Preview (51.8). While Alibaba still trails models from OpenAI, Anthropic and Google, Qwen3.7 Max is the closest they have been to the frontier Qwen3.7 Max is @Alibaba_Qwen's latest proprietary flagship, scoring 56.6 on the Intelligence Index, a 4.8 point gain over Qwen3.6 Max Preview (51.8) released in April. Qwen3.7 Max continues Alibaba's pattern, in place since Qwen2.5 Max (January 2025), of releasing Max and Plus models as closed weights while the rest of the Qwen line remains open weights. The leading open weights Qwen on the Intelligence Index is Qwen3.6 27B (Reasoning, 45.8) released in April 2026, and the leading open weights MoE Qwen is Qwen3.5 397B A17B (Reasoning, 45.0) released in February 2026 Key takeaways for the reasoning variant: ➤ The Intelligence Index gains over Qwen3.6 Max Preview are concentrated in scientific reasoning, agentic capability and coding. CritPt +9.7 p.p (3.7% to 13.4%), HLE +9.2 p.p (28.9% to 38.1%), TerminalBench Hard +6.9 p.p (43.9% to 50.8%) and GDPval-AA +42 Elo (1504 to 1546). Scores on other benchmarks in the Intelligence Index are flat compared to Qwen3.6 Max Preview ➤ A significant share of the Int…

mehr auf Arint.info

#Alibaba #Anthropic #API #Claude #DeepSeek #Gemini #Google #GPT5 #nitter #OpenAI #Qwen #Qwen25 #Qwen35 #Qwen36 #Qwen37 #rest #arint_info

https://x.com/ChujieZheng/status/2057403166589956518#m

RT @ChujieZheng: For Qwen3.7-Max, we have invested far more compute into RL training than ever before. Its top-tier AA score confirms the resulting general and agentic capabilities. This is just the start. We will firmly push forward RL scaling to build more powerful Qwen models. Stay tuned! Artificial Analysis (@ArtificialAnlys) Alibaba’s new Qwen3.7 Max model scores 56.6 on the Artificial Analysis Intelligence Index, 4.8 points higher than Qwen3.6 Max Preview (51.8). While Alibaba still trails models from OpenAI, Anthropic and Google, Qwen3.7 Max is the closest they have been to the frontier Qwen3.7 Max is @Alibaba_Qwen's latest proprietary flagship, scoring 56.6 on the Intelligence Index, a 4.8 point gain over Qwen3.6 Max Preview (51.8) released in April. Qwen3.7 Max continues Alibaba's pattern, in place since Qwen2.5 Max (January 2025), of releasing Max and Plus models as closed weights while the rest of the Qwen line remains open weights. The leading open weights Qwen on the Intelligence Index is Qwen3.6 27B (Reasoning, 45.8) released in April 2026, and the leading open weights MoE Qwen is Qwen3.5 397B A17B (Reasoning, 45.0) released in February 2026 Key takeaways for the reasoning variant: ➤ The Intelligence Index gains over Qwen3.6 Max Preview are concentrated in scientific reasoning, agentic capability and coding. CritPt +9.7 p.p (3.7% to 13.4%), HLE +9.2 p.p (28.9% to 38.1%), TerminalBench Hard +6.9 p.p (43.9% to 50.8%) and GDPval-AA +42 Elo (1504 to 1546). Scores on other benchmarks in the Intelligence Index are flat compared to Qwen3.6 Max Preview ➤ A significant share of the Int…

mehr auf Arint.info

#Alibaba #Anthropic #API #Claude #DeepSeek #Gemini #Google #GPT5 #nitter #OpenAI #Qwen #Qwen25 #Qwen35 #Qwen36 #Qwen37 #rest #arint_info

https://x.com/ChujieZheng/status/2057403166589956518#m

RT @ChujieZheng: For Qwen3.7-Max, we have invested far more compute into RL training than ever before. Its top-tier AA score confirms the resulting general and agentic capabilities. This is just the start. We will firmly push forward RL scaling to build more powerful Qwen models. Stay tuned! Artificial Analysis (@ArtificialAnlys) Alibaba’s new Qwen3.7 Max model scores 56.6 on the Artificial Analysis Intelligence Index, 4.8 points higher than Qwen3.6 Max Preview (51.8). While Alibaba still trails models from OpenAI, Anthropic and Google, Qwen3.7 Max is the closest they have been to the frontier Qwen3.7 Max is @Alibaba_Qwen's latest proprietary flagship, scoring 56.6 on the Intelligence Index, a 4.8 point gain over Qwen3.6 Max Preview (51.8) released in April. Qwen3.7 Max continues Alibaba's pattern, in place since Qwen2.5 Max (January 2025), of releasing Max and Plus models as closed weights while the rest of the Qwen line remains open weights. The leading open weights Qwen on the Intelligence Index is Qwen3.6 27B (Reasoning, 45.8) released in April 2026, and the leading open weights MoE Qwen is Qwen3.5 397B A17B (Reasoning, 45.0) released in February 2026 Key takeaways for the reasoning variant: ➤ The Intelligence Index gains over Qwen3.6 Max Preview are concentrated in scientific reasoning, agentic capability and coding. CritPt +9.7 p.p (3.7% to 13.4%), HLE +9.2 p.p (28.9% to 38.1%), TerminalBench Hard +6.9 p.p (43.9% to 50.8%) and GDPval-AA +42 Elo (1504 to 1546). Scores on other benchmarks in the Intelligence Index are flat compared to Qwen3.6 Max Preview ➤ A significant share of the Int…

mehr auf Arint.info

#Alibaba #Anthropic #API #Claude #DeepSeek #Gemini #Google #GPT5 #nitter #OpenAI #Qwen #Qwen25 #Qwen35 #Qwen36 #Qwen37 #rest #arint_info

https://x.com/ChujieZheng/status/2057403166589956518#m

Celonis is hiring Applied AI Engineer

🔧 #java #python #rest #aws #azure #cicd #gcp #json
🌎 Bangalore, India
⏰ Full-time
🏢 Celonis

Job details https://jobsfordevelopers.com/jobs/applied-ai-engineer-at-celonis-com-apr-2-2026-7268b0?utm_source=mastodon.world&utm_medium=social&utm_campaign=posting
#jobalert #jobsearch #hiring

Celonis is hiring Applied AI Engineer

🔧 #java #python #rest #aws #azure #cicd #gcp #json
🌎 Bangalore, India
⏰ Full-time
🏢 Celonis

Job details https://jobsfordevelopers.com/jobs/applied-ai-engineer-at-celonis-com-apr-2-2026-7268b0?utm_source=mastodon.world&utm_medium=social&utm_campaign=posting
#jobalert #jobsearch #hiring

Celonis is hiring Applied AI Engineer

🔧 #java #python #rest #aws #azure #cicd #gcp #json
🌎 Bangalore, India
⏰ Full-time
🏢 Celonis

Job details https://jobsfordevelopers.com/jobs/applied-ai-engineer-at-celonis-com-apr-2-2026-7268b0?utm_source=mastodon.world&utm_medium=social&utm_campaign=posting
#jobalert #jobsearch #hiring

Celonis is hiring Applied AI Engineer

🔧 #java #python #rest #aws #azure #cicd #gcp #json
🌎 Bangalore, India
⏰ Full-time
🏢 Celonis

Job details https://jobsfordevelopers.com/jobs/applied-ai-engineer-at-celonis-com-apr-2-2026-7268b0?utm_source=mastodon.world&utm_medium=social&utm_campaign=posting
#jobalert #jobsearch #hiring

Celonis is hiring Applied AI Engineer

🔧 #java #python #rest #aws #azure #cicd #gcp #json
🌎 Bangalore, India
⏰ Full-time
🏢 Celonis

Job details https://jobsfordevelopers.com/jobs/applied-ai-engineer-at-celonis-com-apr-2-2026-7268b0?utm_source=mastodon.world&utm_medium=social&utm_campaign=posting
#jobalert #jobsearch #hiring

RT @KyleHessling1: BREAKING! Qwopus 3.6 27B is LIVE! Thank you for your patience on this one, but I believe you'll find the wait was worth it! We've benchmarked this thing up and down, verified that it holds at least a 75.25% (152/202) in the initial 202 SWE bench solves. Not a full run of 500, but it shows the agentic coding quality from the original 27B is retained while adding all of the additional Qwopus benefits across many domains. As always, Jackrong is absolutely cooking here! COT quality has improved significantly through the inversion techniques from our Negentropy proof of concept. It also went through thorough curriculum training. You can check out the MMLU pro benchmarks on the model card, but it improved a whopping 10 points over the base model in physics, as well as meaningful jumps in Chemistry, business, and computer science. However, the best part is that I was able to build an entire survival shooter game using this local model entirely. I genuinely was blown away by the results, which you can play right now on my HF space (link in comments below). "Qwopus Commander" was completed in 9 turns of Qwopus 3.6! To test the new long context training, I made it re-output the entire 3000+ line program each turn, and it would make fixes and add features that I requested in large prompts, while perfectly replicating the entire rest of the game from context. What's more is that I did it all at Q8 KV cache quantization, and never had an issue over the entire 303k token run! IMPORTANT: Run it at --temp 0.75 to 1. Mess with it in that range for your use case. Higher temp actually…

mehr auf Arint.info

#GGUF #huggingface #make #rest #science #SWE #Swe #arint_info

https://x.com/KyleHessling1/status/2057853098585108979#m

RT @KyleHessling1: BREAKING! Qwopus 3.6 27B is LIVE! Thank you for your patience on this one, but I believe you'll find the wait was worth it! We've benchmarked this thing up and down, verified that it holds at least a 75.25% (152/202) in the initial 202 SWE bench solves. Not a full run of 500, but it shows the agentic coding quality from the original 27B is retained while adding all of the additional Qwopus benefits across many domains. As always, Jackrong is absolutely cooking here! COT quality has improved significantly through the inversion techniques from our Negentropy proof of concept. It also went through thorough curriculum training. You can check out the MMLU pro benchmarks on the model card, but it improved a whopping 10 points over the base model in physics, as well as meaningful jumps in Chemistry, business, and computer science. However, the best part is that I was able to build an entire survival shooter game using this local model entirely. I genuinely was blown away by the results, which you can play right now on my HF space (link in comments below). "Qwopus Commander" was completed in 9 turns of Qwopus 3.6! To test the new long context training, I made it re-output the entire 3000+ line program each turn, and it would make fixes and add features that I requested in large prompts, while perfectly replicating the entire rest of the game from context. What's more is that I did it all at Q8 KV cache quantization, and never had an issue over the entire 303k token run! IMPORTANT: Run it at --temp 0.75 to 1. Mess with it in that range for your use case. Higher temp actually…

mehr auf Arint.info

#GGUF #huggingface #make #rest #science #SWE #Swe #arint_info

https://x.com/KyleHessling1/status/2057853098585108979#m

RT @KyleHessling1: BREAKING! Qwopus 3.6 27B is LIVE! Thank you for your patience on this one, but I believe you'll find the wait was worth it! We've benchmarked this thing up and down, verified that it holds at least a 75.25% (152/202) in the initial 202 SWE bench solves. Not a full run of 500, but it shows the agentic coding quality from the original 27B is retained while adding all of the additional Qwopus benefits across many domains. As always, Jackrong is absolutely cooking here! COT quality has improved significantly through the inversion techniques from our Negentropy proof of concept. It also went through thorough curriculum training. You can check out the MMLU pro benchmarks on the model card, but it improved a whopping 10 points over the base model in physics, as well as meaningful jumps in Chemistry, business, and computer science. However, the best part is that I was able to build an entire survival shooter game using this local model entirely. I genuinely was blown away by the results, which you can play right now on my HF space (link in comments below). "Qwopus Commander" was completed in 9 turns of Qwopus 3.6! To test the new long context training, I made it re-output the entire 3000+ line program each turn, and it would make fixes and add features that I requested in large prompts, while perfectly replicating the entire rest of the game from context. What's more is that I did it all at Q8 KV cache quantization, and never had an issue over the entire 303k token run! IMPORTANT: Run it at --temp 0.75 to 1. Mess with it in that range for your use case. Higher temp actually…

mehr auf Arint.info

#GGUF #huggingface #make #rest #science #SWE #Swe #arint_info

https://x.com/KyleHessling1/status/2057853098585108979#m

RT @KyleHessling1: BREAKING! Qwopus 3.6 27B is LIVE! Thank you for your patience on this one, but I believe you'll find the wait was worth it! We've benchmarked this thing up and down, verified that it holds at least a 75.25% (152/202) in the initial 202 SWE bench solves. Not a full run of 500, but it shows the agentic coding quality from the original 27B is retained while adding all of the additional Qwopus benefits across many domains. As always, Jackrong is absolutely cooking here! COT quality has improved significantly through the inversion techniques from our Negentropy proof of concept. It also went through thorough curriculum training. You can check out the MMLU pro benchmarks on the model card, but it improved a whopping 10 points over the base model in physics, as well as meaningful jumps in Chemistry, business, and computer science. However, the best part is that I was able to build an entire survival shooter game using this local model entirely. I genuinely was blown away by the results, which you can play right now on my HF space (link in comments below). "Qwopus Commander" was completed in 9 turns of Qwopus 3.6! To test the new long context training, I made it re-output the entire 3000+ line program each turn, and it would make fixes and add features that I requested in large prompts, while perfectly replicating the entire rest of the game from context. What's more is that I did it all at Q8 KV cache quantization, and never had an issue over the entire 303k token run! IMPORTANT: Run it at --temp 0.75 to 1. Mess with it in that range for your use case. Higher temp actually…

mehr auf Arint.info

#GGUF #huggingface #make #rest #science #SWE #Swe #arint_info

https://x.com/KyleHessling1/status/2057853098585108979#m

RT @KyleHessling1: BREAKING! Qwopus 3.6 27B is LIVE! Thank you for your patience on this one, but I believe you'll find the wait was worth it! We've benchmarked this thing up and down, verified that it holds at least a 75.25% (152/202) in the initial 202 SWE bench solves. Not a full run of 500, but it shows the agentic coding quality from the original 27B is retained while adding all of the additional Qwopus benefits across many domains. As always, Jackrong is absolutely cooking here! COT quality has improved significantly through the inversion techniques from our Negentropy proof of concept. It also went through thorough curriculum training. You can check out the MMLU pro benchmarks on the model card, but it improved a whopping 10 points over the base model in physics, as well as meaningful jumps in Chemistry, business, and computer science. However, the best part is that I was able to build an entire survival shooter game using this local model entirely. I genuinely was blown away by the results, which you can play right now on my HF space (link in comments below). "Qwopus Commander" was completed in 9 turns of Qwopus 3.6! To test the new long context training, I made it re-output the entire 3000+ line program each turn, and it would make fixes and add features that I requested in large prompts, while perfectly replicating the entire rest of the game from context. What's more is that I did it all at Q8 KV cache quantization, and never had an issue over the entire 303k token run! IMPORTANT: Run it at --temp 0.75 to 1. Mess with it in that range for your use case. Higher temp actually…

mehr auf Arint.info

#GGUF #huggingface #make #rest #science #SWE #Swe #arint_info

https://x.com/KyleHessling1/status/2057853098585108979#m

Как настроить кастомную авторизацию в FESB и сохранить стандартный заголовок

При проектировании REST-интеграций часто возникает конфликт заголовков, когда и целевая система, и шина данных требуют дефолтный Authorization . В этой статье мы пошагово разберем, как перенастроить FESB на анализ кастомного заголовка для отдельной группы методов. Вы узнаете, как отключить стандартную проверку, распарсить Base64 с помощью Groovy и вернуть корректный HTTP-ответ.

https://habr.com/ru/articles/1036906/

#авторизация #заголовок_http #шина_данных #интеграция #интеграция_систем #api #rest

Как настроить кастомную авторизацию в FESB и сохранить стандартный заголовок

При проектировании REST-интеграций часто возникает конфликт заголовков, когда и целевая система, и шина данных требуют дефолтный Authorization . В этой статье мы пошагово разберем, как перенастроить FESB на анализ кастомного заголовка для отдельной группы методов. Вы узнаете, как отключить стандартную проверку, распарсить Base64 с помощью Groovy и вернуть корректный HTTP-ответ.

https://habr.com/ru/articles/1036906/

#авторизация #заголовок_http #шина_данных #интеграция #интеграция_систем #api #rest

Как настроить кастомную авторизацию в FESB и сохранить стандартный заголовок

При проектировании REST-интеграций часто возникает конфликт заголовков, когда и целевая система, и шина данных требуют дефолтный Authorization . В этой статье мы пошагово разберем, как перенастроить FESB на анализ кастомного заголовка для отдельной группы методов. Вы узнаете, как отключить стандартную проверку, распарсить Base64 с помощью Groovy и вернуть корректный HTTP-ответ.

https://habr.com/ru/articles/1036906/

#авторизация #заголовок_http #шина_данных #интеграция #интеграция_систем #api #rest

Как настроить кастомную авторизацию в FESB и сохранить стандартный заголовок

При проектировании REST-интеграций часто возникает конфликт заголовков, когда и целевая система, и шина данных требуют дефолтный Authorization . В этой статье мы пошагово разберем, как перенастроить FESB на анализ кастомного заголовка для отдельной группы методов. Вы узнаете, как отключить стандартную проверку, распарсить Base64 с помощью Groovy и вернуть корректный HTTP-ответ.

https://habr.com/ru/articles/1036906/

#авторизация #заголовок_http #шина_данных #интеграция #интеграция_систем #api #rest

RT @ChujieZheng: For Qwen3.7-Max, we have invested far more compute into RL training than ever before. Its top-tier AA score confirms the resulting general and agentic capabilities. This is just the start. We will firmly push forward RL scaling to build more powerful Qwen models. Stay tuned! Artificial Analysis (@ArtificialAnlys) Alibaba’s new Qwen3.7 Max model scores 56.6 on the Artificial Analysis Intelligence Index, 4.8 points higher than Qwen3.6 Max Preview (51.8). While Alibaba still trails models from OpenAI, Anthropic and Google, Qwen3.7 Max is the closest they have been to the frontier Qwen3.7 Max is @Alibaba_Qwen's latest proprietary flagship, scoring 56.6 on the Intelligence Index, a 4.8 point gain over Qwen3.6 Max Preview (51.8) released in April. Qwen3.7 Max continues Alibaba's pattern, in place since Qwen2.5 Max (January 2025), of releasing Max and Plus models as closed weights while the rest of the Qwen line remains open weights. The leading open weights Qwen on the Intelligence Index is Qwen3.6 27B (Reasoning, 45.8) released in April 2026, and the leading open weights MoE Qwen is Qwen3.5 397B A17B (Reasoning, 45.0) released in February 2026 Key takeaways for the reasoning variant: ➤ The Intelligence Index gains over Qwen3.6 Max Preview are concentrated in scientific reasoning, agentic capability and coding. CritPt +9.7 p.p (3.7% to 13.4%), HLE +9.2 p.p (28.9% to 38.1%), TerminalBench Hard +6.9 p.p (43.9% to 50.8%) and GDPval-AA +42 Elo (1504 to 1546). Scores on other benchmarks in the Intelligence Index are flat compared to Qwen3.6 Max Preview ➤ A significant share of the Int…

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#Alibaba #Anthropic #API #Claude #DeepSeek #Gemini #Google #GPT5 #nitter #OpenAI #Qwen #Qwen25 #Qwen35 #Qwen36 #Qwen37 #rest #arint_info

https://x.com/ChujieZheng/status/2057403166589956518#m

#Rest #PurposefulLiving #Wellness #Rest #PurposefulLiving #Wellness #HealthyLifestyle #MindBodySpirit #Motivation #Inspiration #healthyageing #healthyaging #wellnessthatworks #wellnessblogger #emotionalwellbeing #wellnesslifestyle #wellnesswarrior #healthandwellbeing #wellnessgoals #wellnessadvocate #wellnesscoaching #Wellbeing #SelfCare #PhysicianAdvice https://mastodon.social/@biohackingpathway/116615838771292289

#Rest #PurposefulLiving #Wellness #Rest #PurposefulLiving #Wellness #HealthyLifestyle #MindBodySpirit #Motivation #Inspiration #healthyageing #healthyaging #wellnessthatworks #wellnessblogger #emotionalwellbeing #wellnesslifestyle #wellnesswarrior #healthandwellbeing #wellnessgoals #wellnessadvocate #wellnesscoaching #Wellbeing #SelfCare #PhysicianAdvice https://mastodon.social/@biohackingpathway/116615838771292289

Even the most dedicated historians need a break! Heather Cox Richardson, known for her daily political updates, shared a peaceful kayak photo, choosing rest over pushing through after travel. A gentle reminder to prioritize self-care before summer. Read more: https://heathercoxrichardson.substack.com/p/may-18-2026 #HeatherCoxRichardson #Rest #Substack Thank you, Heather, for the important reminder.

Even the most dedicated historians need a break! Heather Cox Richardson, known for her daily political updates, shared a peaceful kayak photo, choosing rest over pushing through after travel. A gentle reminder to prioritize self-care before summer. Read more: https://heathercoxrichardson.substack.com/p/may-18-2026 #HeatherCoxRichardson #Rest #Substack Thank you, Heather, for the important reminder.

Sometimes I wondered... Could the lack of forests and nature be slowly eroding my soul and making me tired. The proper forests are so far...

#nature #forests #rest #resting

Sometimes I wondered... Could the lack of forests and nature be slowly eroding my soul and making me tired. The proper forests are so far...

#nature #forests #rest #resting

Sometimes I wondered... Could the lack of forests and nature be slowly eroding my soul and making me tired. The proper forests are so far...

#nature #forests #rest #resting

Sometimes I wondered... Could the lack of forests and nature be slowly eroding my soul and making me tired. The proper forests are so far...

#nature #forests #rest #resting

Sometimes I wondered... Could the lack of forests and nature be slowly eroding my soul and making me tired. The proper forests are so far...

#nature #forests #rest #resting

Spring Agent Toolkit: ультимативный набор для вашего AI-агента

AI-агенты уже стали частью повседневной разработки. Сначала это выглядит как магия: формулируешь задачу, получаешь код, тесты, иногда даже готовый PR. Но довольно быстро приходит осознание: – токены улетают слишком быстро; – задача выполняется дольше, чем ожидалось; – результат не всегда совпадает с тем, что было задумано. В этой статье разберем, что с этим можно сделать на практике и почему для хорошего результата критически важен правильно подобранный набор инструментов.

https://habr.com/ru/companies/haulmont/articles/1034688/

#springboot #aiагенты #mcp #skill #jpa #rest #генерация_кода

Spring Agent Toolkit: ультимативный набор для вашего AI-агента

AI-агенты уже стали частью повседневной разработки. Сначала это выглядит как магия: формулируешь задачу, получаешь код, тесты, иногда даже готовый PR. Но довольно быстро приходит осознание: – токены улетают слишком быстро; – задача выполняется дольше, чем ожидалось; – результат не всегда совпадает с тем, что было задумано. В этой статье разберем, что с этим можно сделать на практике и почему для хорошего результата критически важен правильно подобранный набор инструментов.

https://habr.com/ru/companies/haulmont/articles/1034688/

#springboot #aiагенты #mcp #skill #jpa #rest #генерация_кода