Meta names Shengjia Zhao as chief scientist of AI superintelligence unit

✨TodayOnAI’s Daily Drop

• Meta names Shengjia Zhao as chief scientist of AI superintelligence unit

• Google is testing a vibe-coding app called Opal

• White House Eyes AI to Slash Federal Rules by Half

• 💬 Let’s Fix This Prompt

• 🧰 Today’s AI Toolbox Pick

Meta

Meta names Shengjia Zhao as chief scientist of AI superintelligence unit

🚀 TodayOnAI Insight: Meta has appointed former OpenAI researcher Shengjia Zhao as Chief Scientist of its new Meta Superintelligence Labs, bolstering its efforts to develop frontier AI models. Zhao, a key contributor to GPT-4 and OpenAI’s o1 reasoning model, will lead research under Alexandr Wang’s broader leadership.

🔍 Key Takeaways:

• Zhao named Chief Scientist at Meta Superintelligence Labs (MSL): He co-founded the unit and has led research from inception.

• Strong research pedigree: Zhao was instrumental in OpenAI’s GPT-4, ChatGPT, and o1 reasoning model development.

• MSL leadership team expands: Zhao complements Wang, Scale AI’s former CEO, who leads MSL despite lacking a research background.

• Top-tier recruitment drive: Meta has hired from OpenAI, DeepMind, Anthropic, Apple, and its own FAIR and generative AI teams.

• Massive compute investment: By 2026, MSL will train models on Meta’s 1 GW Prometheus cluster—one of the world’s most powerful AI infrastructures.

💡 Why This Stands Out: Meta’s AI ambitions are shifting from experimental research toward aggressive competition with OpenAI and Google. Zhao’s appointment formalizes a strategy that blends elite research talent with massive infrastructure bets. With FAIR focused on long-term exploration, MSL appears poised to drive Meta’s near-term push into frontier AI. Can Meta’s dual-track approach outpace rivals in a rapidly consolidating field?

Google

Google is testing a vibe-coding app called Opal

🚀 TodayOnAI Insight: Google is testing Opal, an AI coding tool aimed at non-developers, as part of its Google Labs experiments. The move signals Google's entry into the rapidly expanding "vibe-coding" space, where startups and major platforms alike are racing to make app creation accessible via text prompts.

🔍 Key Takeaways:

• Opal enables app building via text prompts, allowing users to generate mini web apps or remix existing ones.

• Visual workflow editor lets users inspect, edit, and expand AI-generated steps, offering more control without requiring code.

• Apps can be published and shared, usable by others via Google accounts—supporting real-world collaboration and feedback.

• Built within Google Labs, Opal is currently limited to U.S. users as part of a test rollout.

• Google joins Canva, Figma, and Replit, all targeting low-code/no-code creation for non-technical audiences.

💡 Why This Stands Out: Google's launch of Opal reinforces a growing trend: AI tools are reshaping software development by shifting power to prompt-driven, visual-first interfaces. As more platforms compete to simplify app creation, the line between developer and user is blurring. The question now is—who will own the go-to interface for building the next billion mini-apps?

AI

White House Eyes AI to Slash Federal Rules by Half

🚀 TodayOnAI Insight: The Department of Government Efficiency (DOGE) is deploying an AI tool to slash federal regulations, aiming to cut half of all mandates if Donald Trump returns to office—a bold experiment in automated deregulation with sweeping policy implications.

🔍 Key Takeaways:

• The DOGE AI Deregulation Decision Tool is designed to evaluate ~200,000 federal regulations and flag those no longer legally required.

• A July 1 PowerPoint reviewed by The Washington Post outlines a goal of eliminating half of all federal mandates within a year of Trump’s potential return.

• The tool has already been used to review HUD rules and reportedly authored “100% of deregulations” at the Consumer Financial Protection Bureau.

• While no formal plan is approved, the White House praised the DOGE team as “the best and brightest.”

• DOGE, once led by Elon Musk, previously developed an error-prone AI system that hallucinated VA contract figures.

💡 Why This Stands Out: Automating regulatory review with AI could dramatically accelerate deregulatory agendas, bypassing traditional legal and bureaucratic safeguards. The scale of this initiative—and its reliance on still-maturing tech—raises urgent questions about transparency, accountability, and the boundaries of machine-driven policymaking.

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🧰 Today’s AI Toolbox Pick

• 🍋LemonSqueezy (Finance Tool): Handles the tax compliance burden so you can focus on more revenue with less headache.

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