@DeepLearn007
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Imtiaz Adam CS #AI Postgrad |#Strategy #MachineLearning RSI Evolutionary Neurosymbolic |#RL #Agentic | #LLM Liberal | MBA alum @morganstanley @LBS @Columbia_Biz
Joined September 2012
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AI retweeted
Introducing Ling-3.1-flash-1019 🚀
It scores 44 on the Artificial Analysis Intelligence Index, up from 41 for Ling-3.1-flash. Gains in agentic work: AA-Briefcase ~1400→1524 Elo and AutomationBench-AA 62%→68%.
API access and open weights coming soon. Stay tuned.
AI retweeted
Scientists have discovered that COVID-19 can directly infect key brain cells responsible for dopamine production, driving them into an aged, 'zombie-like' state.
Researchers have uncovered a striking biological mechanism explaining why many individuals experience persistent brain fog, chronic fatigue, and loss of motivation following a COVID-19 infection.
Studies demonstrate that SARS-CoV-2 can directly target midbrain dopamine neurons—the specialized cells responsible for regulating movement, focus, and reward pathways. Upon infection, these neurons stop functioning normally and enter a state known as cellular senescence. Rather than dying, the infected dopamine cells become non-functional 'zombie' cells, halting dopamine production while actively secreting chemical signals that trigger ongoing localized inflammation.
This unexpected transformation mirrors biological pathways commonly seen in age-related neurodegenerative conditions like Parkinson's disease. By proving that dopamine neurons are uniquely susceptible to the virus, the findings provide a tangible target for medical interventions. Encouragingly, laboratory screens revealed that certain FDA-approved medications can prevent infection and rescue these damaged cells, opening promising new avenues for treating lingering neurological symptoms in long COVID patients.
source: Yang, L., Kim, T. W., Han, Y., Nair, M. S., Harschnitz, O., Zhu, J., Wang, P., Koo, S. Y., Lacko, L. A., ... Chen, S. SARS-CoV-2 infection causes dopaminergic neuron senescence. Cell Stem Cell, 31(2), 196-211.
AI retweeted
JUST IN: OpenAI launches global cybersecurity initiative called “Patch the Planet” after AI helped uncover critical flaws in PHP, a programming language powering millions of websites.
AI retweeted
Effective Immediately, all organizations using PHP for their systems are advised to be prepared for an update addressing two critical vulnerabilities. PHP is widely used for web applications. These vulnerabilities often provide a direct path to the server's file system or database. If an immediate update is not feasible, it is recommend that organizations take the system offline until it can be fully mitigated. NSA will follow up shortly with more specific guidance.
By circa 2035 I envisage advanced AI-enabled robots scaling across manufacturing, retail (warehousing), military and security.
AI retweeted
Aloha!🌺 Meet Ornith-1.5-122B: No Tradeoff Between Strong and Fast
Stronger. Faster. Leaner. Ornith-1.5-122B delivers frontier-level capabilities with exceptional inference efficiency. With superior instruction following, stronger task decomposition, and deeper understanding of real-world workflows, it achieves state-of-the-art performance among open-source models of comparable size, while running on a single NVIDIA DGX card!!
Open weights under the MIT license.
Coding
✅SWE-bench Verified: 0.845
✅TB2.1: 0.813
✅CyberGym: 0.800
✅NL2Repo: 0.512
Agentic
✅HLE: 0.446
✅BrowseComp: 0.785
✅MCP-Atlas: 0.746
✅Toolathlon: 0.708
🤗Hugging Face: huggingface.co/ornith-ai/Orn…
We can’t wait to see what you build with Ornith-1.5-122B.
AI retweeted
Ornith 1.5 122B is available on Ollama! Run it all locally on your device.
ollama run ornith-1.5:122b
Aloha!🌺 Meet Ornith-1.5-122B: No Tradeoff Between Strong and Fast
Stronger. Faster. Leaner. Ornith-1.5-122B delivers frontier-level capabilities with exceptional inference efficiency. With superior instruction following, stronger task decomposition, and deeper understanding of real-world workflows, it achieves state-of-the-art performance among open-source models of comparable size, while running on a single NVIDIA DGX card!!
Open weights under the MIT license.
Coding
✅SWE-bench Verified: 0.845
✅TB2.1: 0.813
✅CyberGym: 0.800
✅NL2Repo: 0.512
Agentic
✅HLE: 0.446
✅BrowseComp: 0.785
✅MCP-Atlas: 0.746
✅Toolathlon: 0.708
🤗Hugging Face: huggingface.co/ornith-ai/Orn…
We can’t wait to see what you build with Ornith-1.5-122B.
AI retweeted
Elon Musk ordered the slowdown of a military-grade version of Starlink relied on by Ukraine, a decision that sparked panic in Kyiv and confusion inside the Trump administration.
Musk has spoken to Putin several times. He has used thousands of responses to boost the reach, following and monetization income of pro-Russian accounts on X making him the prime orchestrator of Russia's propaganda effort in the West.
There can be no doubt that Musk is collaborating with Putin to destroy democracy in order to bring about the kind of technofascist dictatorship advocated by Thiel's 'house philosopher' Curtis Yarvin, and forecast in "The Sovereign Individual" for which Thiel wrote the preface.
Putin doubtless flattered Musk as being one of the handful of individuals capable of ensuring the long term survival of humanity, and played on Musk's rage against wokeness which he blames for his trans son changing gender.
wsj.com/world/ukraine-starli…
AI retweeted
BREAKING: US oil prices rebound on reports stating that other reports claiming the US and Iran have reached a deal are false.
We now have reports on reports that are moving hundreds of billions of dollars in market cap.
AI retweeted
Grateful to @deepseek_ai for releasing DeepInfer, initially built primarily on @vllm_project, under Apache 2.0 and crediting the open-source community!
We've worked hard on DeepSeek V4.1 Flash inference efficiency and will keep improving with ideas from DeepInfer! Stay tuned 🙌
🚀 Introducing DeepInfer, our in-house inference framework, now fully open source!
Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable.
🔗 github.com/deepseek-ai/DeepI…
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AI retweeted
If this is accurate, Elon lied about not having control over Starshield, and he lied about the administration making the decision.
More importantly, why is a private citizen even *able* to make decisions that could hinder US military operations?
Incredible scoop by my @WSJ colleagues: Elon Musk ordered the slowdown of a military-grade version of Starlink relied on by Ukraine, a decision that sparked panic in Kyiv and confusion inside the Trump administration. wsj.com/world/ukraine-starli…
AI retweeted
Breaking: Elon Musk ordered the Starlink slowdown that blindsided Ukraine on.wsj.com/4sgcpBv
AI retweeted
We’ve acquired Orchestra Bio, a platform that helps biopharma teams coordinate the complex process of drug development.
Together, we’ll build on Rosalind, our AI models and tools for life sciences research, to streamline those operations and help new treatments reach patients sooner.
Welcome @ashokaraj_ and team!
openai.com/index/openai-to-a…
AI retweeted
US electricity prices are skyrocketing.
The average price of US residential electricity has risen +11% since January 2025, to 19.6 cents per kilowatt-hour in August 2026, near an all-time high.
Average prices during the first 8 months of 2026 were +40% higher than in the same period of 2019.
The largest increase in residential electricity prices over this period was in Maine, at +90%, followed by California and New York, at nearly +70%.
This comes as the AI boom is intensifying electricity demand, with data centers requiring enormous amounts of electricity to power thousands of chips and cooling systems.
A 1-gigawatt data center can consume as much electricity as 800,000 homes.
As a result, wholesale electricity prices in areas near significant data center activity surged by as much as +267% between 2020 and 2025.
The AI revolution is driving a surge in electricity demand, and households are increasingly feeling the cost.
AI retweeted
Introducing GLM-Legal
Built on GLM-5.3-Flash, GLM-Legal matches frontier models on mainstream legal benchmarks.
Designed for real legal workflows: contract review, evidence analysis, compliance, and more.
Tech Blog: z.ai/blog/glm-legal
Apply for API Access: z.ai/consultation/legal
Try AutoClaw: autoclaw.z.ai
AI retweeted
MiniMax-M3.1-Flash scores 42 on the Artificial Analysis Intelligence Index, 13 points higher than MiniMax-M3 and less than half the cost per task. It scores level with GLM-5.3-Flash but behind DeepSeek V4.1 Flash 1017
MiniMax-M3.1-Flash is @MiniMax_AI's new Flash reasoning model, which we benchmarked at its max effort setting. It scores 42 on the Artificial Analysis Intelligence Index, level with GLM-5.3-Flash (max, 42), just ahead of Gemini 3.8 Flash (high, 41), and behind DeepSeek V4.1 Flash 1017 (max, 45)
Key takeaways:
➤ Complex reasoning improved substantially compared to M3: MiniMax-M3.1-Flash scores 48% on Humanity's Last Exam, ahead of GLM-5.3-Flash (max, 40%) and DeepSeek V4.1 Flash 1017 (max, 43%), and level with Gemini 3.8 Flash (high, 48%). On CritPt it scores 22%, ahead of GLM-5.3-Flash (15%) and Gemini 3.8 Flash (18%) and just behind DeepSeek V4.1 Flash 1017 (24%). These are up from MiniMax-M3 which scored 39% and 4% respectively
➤ Fewer output tokens, lower cost per task: MiniMax-M3.1-Flash used ~189M output tokens to run the Intelligence Index, considerably fewer than GLM-5.3-Flash (max, ~324M), DeepSeek V4.1 Flash 1017 (max, ~224M) and Gemini 3.8 Flash (high, ~334M). Combined with pricing of $0.15/$0.60 per 1M input/output tokens, this brings its cost to ~$0.22 per Intelligence Index task, vs ~$0.28 for GLM-5.3-Flash, ~$0.26 for DeepSeek V4.1 Flash 1017 and ~$1.24 for Gemini 3.8 Flash, and less than half MiniMax-M3's ~$0.51
➤ High AA-Omniscience accuracy, offset by a high hallucination rate: MiniMax-M3.1-Flash answers 56% of questions correctly on AA-Omniscience, our benchmark measuring factual recall and hallucination, vs 28% for GLM-5.3-Flash (max) and 43% for DeepSeek V4.1 Flash 1017 (max). It attempts almost every question, resulting in a hallucination rate of 93% and an overall score of 16 on AA-Omniscience
Key model details:
➤ Context window: 1M tokens
➤ Multimodality: Text and image input, text output
➤ Pricing: $0.15/$0.60 per 1M input/output tokens, with cached input at $0.015/M
➤ Availability: MiniMax first-party API, with MiniMax announcing an open weights release on October 23rd
➤ Licensing: Closed weights currently, with MiniMax announcing a weights release on October 23rd
AI retweeted
GLM 5.3’s biggest leap came from post-training alone.
“GLM 5.3 was built entirely by post-training the previous model. For me, that was a wake-up call.”
“Post-training is far more GPU-efficient than pre-training from scratch. Plenty of companies can’t afford to train a model from scratch, but they have proprietary data. They can post-train themselves and beat some of the closed models.”
“There’s still so much juice left to squeeze from post-training. We compared GLM 5.3’s cyber capabilities with 5.2, and it’s a night and day difference. That’s all just post-training.”