Sources:
Anthropic, When AI builds itself:
https://anthropic.com/institute/recursive-self-improvement
… SkillOpt (arXiv): https://arxiv.org/abs/2605.23904 SkillSmith (arXiv): https://arxiv.org/abs/2606.01314 MOSS (arXiv): https://arxiv.org/abs/2605.22794 Co-Scientist, Google DeepMind: https://deepmind.google/blog/co-scientist-a-multi-agent-ai-partner-to-accelerate-research/
… Gary Marcus, No need to panic
RESEARCH
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AI Self-Improvement: New Advances and Outlooks
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Karpathy’s 2015 RNN coding experiments and 2017 gradient descent advances
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2015: Karpathy publishes one of the earliest experiments (if not the first public article/blog with practical artifacts) on language models for coding (The Unreasonable Effectiveness of Recurrent Neural Networks). 2017: @karpathy again: gradient descent can write code better
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Making AI trustworthy for genuine scientific discovery
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How do we make AI trustworthy enough for genuine scientific discovery? @Stanford and @SLAClab Associate Professor Ben Nachman – who is also the co-director for the Center for Decoding the Universe – shares his insights from the AI+Science conference ↘️ pic.twitter.com/2t4GlkIjPM
— Stanford HAI (@StanfordHAI) 5 juin 2026How do we make AI trustworthy enough for genuine scientific discovery? @Stanford and @SLAClab Associate Professor Ben Nachman – who is also the co-director for the Center for Decoding the Universe – shares his insights from the AI+Science conference
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NVIDIA Nemotron Coalition grows with new AI partners
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The NVIDIA Nemotron Coalition continues to grow. We're excited to welcome new members: @hcompany_ai
, @NousResearch
, and @PrimeIntellect
. And a big thank you to our existing members: @bfl_ai
, @cursor_ai
, @LangChain
, @MistralAI
, NAVER Cloud, @perplexity_ai
, @ReflectionAI_
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Google DeepMind releases Gemma 4 QAT models for on-device use
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Google DeepMind released new Gemma 4 QAT models that make the model family much more efficient for local, on-device use. Using Quantization-Aware Training, the models are trained with compression in mind, which reduces memory needs while preserving more quality than standard
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EdgeRazor: AI Models Run on Phones via Mixed-Precision Quantization
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Wow, AI models can run on your phone without losing smarts! Researchers from Nanjing University and Microsoft AI present EdgeRazor — a lightweight framework that uses mixed-precision quantization-aware distillation. It assigns different bit-widths to different parts of the
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Sakana AI launches RSI Lab in Tokyo for self-improving AI systems
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Today, we are officially launching the Sakana AI RSI Lab in Tokyo to build open-ended, adaptive AI systems that collectively self-improve. I am incredibly proud of our team’s work over the past 2 years, shipping the breakthrough research that laid the foundations for this moment.
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Sakana AI launches Recursive Self-Improvement Lab in Tokyo
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Building AI that Builds AI: Introducing the Sakana AI RSI Lab https://
sakana.ai/rsi-lab Today, we are announcing the Sakana AI Recursive Self-Improvement (RSI) Lab: a dedicated research group in Tokyo tasked with redesigning the AI development process itself using AI. While -
Sarvam AI builds full-stack ‘Made in India’ AI platform with NVIDIA H100 GPUs
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Sovereign AI at population scale isn’t theory anymore, it’s shipping. Sarvam AI is building a full-stack, “Made in India” AI platform that: Trains 100B+ parameter MoE models efficiently across 4,096+ NVIDIA H100 GPUs Delivers millisecond-level, multilingual voice
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Code2LoRA: Hypernetwork Adapters for Code Models
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Code2LoRA
— AK (@_akhaliq) 5 juin 2026
Hypernetwork-Generated Adapters for Code Language Models under Software Evolution pic.twitter.com/e4vq1C83mYCode2LoRA
Hypernetwork-Generated Adapters for Code Language Models under Software Evolution