One step closer to fully generative graphics at 60 leather jackets per second:
AI
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Video-to-Video AI Crosses Uncanny Valley in Gaming
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Big moment. You can cross the uncanny valley in video games by using real-time video-to-video AI.
— Bilawal Sidhu (@bilawalsidhu) 16 mars 2026
You get the best of coherence & control from classical 3d engines, then use generative AI to take it all the way. https://t.co/sr9zol6sJLBig moment. You can cross the uncanny valley in video games by using real-time video-to-video AI. You get the best of coherence & control from classical 3d engines, then use generative AI to take it all the way.
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Claude Code Commits Tracker Shows Vertical Growth in Software Industry
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We made a tracker to follow how the software industry is changing Priit @ Amperly AI productivity (@amperlycom) Claude Code commits are going vertical. I made a tracker to record the liftoff coremention.com/blog/claude-… — https://nitter.net/amperlycom/status/2033626364314849448#m
→ View original post on X — @coremention, 2026-03-16 19:30 UTC
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Groq 3 LPX Compute Tray Delivers 35x Token Generation Boost
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Groq 3 LPX Compute Tray is here > A token accelerator > 35x increase in token generation
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AI Filter Concerns Impact Artistic Vision Gaming
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This looks very bad and significantly changes the artistic vision of a game. Looks like a random AI filter and gives it that AI look. But likely a first step to improvement so I’m still hopeful. https://t.co/l25HHUxub9
— Varun Mayya (@waitin4agi_) 16 mars 2026This looks very bad and significantly changes the artistic vision of a game. Looks like a random AI filter and gives it that AI look. But likely a first step to improvement so I’m still hopeful.
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Why AI’s Impact on Cancer Research Has Been Limited
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F Cancer Why has AI had so little impact on Cancer? New essay, link below.
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Jensen Huang Projects $1 Trillion NVIDIA Revenue by 2027
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the Buy a GPU thesis proves true once again Jensen is expecting $1 TRILLION USD revenue through 2027
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LFM2 Models Dominate Fine-Tuneability Benchmark Among Small LLMs
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Very interesting results about the fine-tunability of different models. 👀 LFM2 is more flexible than alternatives. It also confirms some common knowledge about RL degrading fine-tuneability. Jacek Golebiowski (@j_golebiowski) We benchmarked 15 small language models across 9 tasks to find out which one you should actually fine-tune. The most surprising result: Liquid AI's LFM2-350M ranked #1 for tunability. 350M parameters, absorbing training signal more effectively than models 20x its size. The entire LFM2 family swept the top 3 spots. No other architecture came close. LFM2-350M: avg rank 2.11 (±0.89) LFM2-1.2B: avg rank 3.44 LFM2.5-1.2B-Instruct: avg rank 4.89 That tight CI means it's consistent across every task type, not just a few lucky benchmarks. — https://nitter.net/j_golebiowski/status/2033611679645266280#m
→ View original post on X — @maximelabonne, 2026-03-16 19:06 UTC
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CoPaw: Personal AI Assistant for Cloud and Local Deployment
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GitHub – agentscope-ai/CoPaw: Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities. https://
buff.ly/mkQDquu
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Elsevier Ranks Top Three for Women and Diversity Awards
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Financial Times: Comparably announces the 2026 Best Company Outlook, Companies for Women, and Companies for Diversity Awards. #Elsevier ranked in the top 3 for all three awards. https://
markets.ft.com/data/announce/
detail?dockey=600-202603101040BIZWIRE_USPRX____20260310_BW028766-1
… via @FT #Women #GreatPlacetoWork