Greetings,

There’s an exciting competition happening in the AI world, and the outcome will surely have an impact on the industry. It’s open-source VS closed-source, walled AI gardens VS free-for-all AI development. Closed-source is winning for now but open, with Meta at the forefront, is getting very close.

• Finally, a worthy contender – fine-tuned Code Llama defeats GPT-4 (by a small margin, but still counts) on the HumanEval benchmark, showcasing the power of open-source LLM research. - Phind
  
  
• This isn’t even the final form of LLMs – explore the 10 biggest challenges that need to be solved to unlock the full power of LLMs, including reduction of hallucinations, design of new model architectures, or making agents usable. - Chip Huyen
  
  
• Mojo could dethrone Python as the fastest language for AI – its creators are now explaining how they arrived at the claim that it’s 35,000x faster than Python, but people won’t be able to verify this until its release in early September. - Modular
  
  
• From a survey of 1,500 AI decision-makers – 69% have at least one project in production and see AI as a revenue driver (not cost saver), top challenges are data management, security, compute performance, and legacy infrastructures. - Weka
  
  
• 92% of US executives agree that people skills are more important than ever, 51% are excited about AI but not yet sure how they’ll extract value from it, and only 4% are planning to reduce headcount because of it. - LinkedIn
  
  
• AI is about to upend science and enable moonshot discoveries, and ex-Google CEO Eric Schmidt wants to accelerate this process by funding a nonprofit that will provide top-level compute to scientists and AI researchers. - Semafor
  
  
• A bit of hot gossip – an expert from OpenAI overheard that Llama 3 could be as powerful as GPT-4 and Meta will open-source it just like the previous versions, causing some people to worry that this will make AI safety research meaningless. - X post 1, X post 2

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