It’s an exciting summer for many data scientists as they get massive pay raises—and an expensive one for Meta CEO Mark Zuckerberg. If a price tag were to be put on his summer spending spree, it could total up to $1.4 billion. Probably a better use of his money than “renting out” Venice like Amazon founder Jeff Bezos did for his nuptials, as this bill is all about getting Meta out of its AI rut.

Meta’s previous AI team just wasn’t cutting it, and progress was slowing for their open-source Llama LLM’s. So what do you do when you have virtually unlimited resources? Follow the lead of the oligarchs and sheiks that buy sports teams: just buy a better team.

What he’s hiring for: Meta Superintelligence Labs, whose mission is to build “AI that can handle tasks at the same level as, or better than, humans.”

Where the hires came from: OpenAI, Google DeepMind, Anthropic, Apple, Scale AI, GitHub, Sesame AI, Google Research, and Safe Superintelligence. (Curiously, no poaches yet from Amazon or Microsoft.)

Notably, Nat Friedman (former GitHub CEO) will co-lead Superintelligence Labs with new Chief AI Officer Alexandr Wang (founder of Scale AI). And how will co-lead play out when you’ve got two heavyweight entrepreneurs in the same room? Sounds like a “too many cooks in the kitchen” situation.

OpenAI CEO Sam Altman’s response didn’t mince words in his repose to Meta’s talent grab. “What Meta is doing will, in my opinion, lead to very deep cultural problems,” he said, adding that “Meta is acting in a way that feels somewhat distasteful; I assume things will get even crazier in the future.” Altman positioned his team as purpose-driven rather than profit-driven, saying they’re more missionaries than mercenaries, and that in the end, missionaries will win (sounds like this guy’s played Civ 5).

Either way, Zuckerberg’s following a familiar playbook: bring together the smartest people in the room and see what they can build. If you’re craving names and AI research contributions, Wang went ahead and proudly posted the AI Avengers lineup on X.

The student who was suspended from Columbia for creating a tool that helped software engineers cheat during interviews didn’t disappear, he built a startup instead. That tool eventually became Cluely, which just announced it has reached $7M in annual recurring revenue.

Its main product is described as an “undetectable AI that sees your screen, hears your calls, and feeds you answers — in real time.” It’s aimed at people who spend a lot of time in interviews, meetings, or other high-stakes conversations.

One feature that stands out: instead of waiting for meeting notes after the call, Cluely gives you real-time insights like suggested follow-up questions or answers to what's being asked. It helps you perform better and stay engaged in conversations.

If real-time help during meetings sounds useful, it might be worth checking out (available in both free and paid tiers). Here’s a demo of the tool.

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It was recently uncovered that 17 computer science papers on arXiv were secretly embedding AI prompts using white text or tiny fonts. The prompts, planted by authors from schools like Columbia and University of Washington, told AI reviewers to give glowing feedback. The hidden praise prompts included buzzwords like “exceptional novelty” and “methodological rigor.” Not everyone took offense, however, as one professor called it a counter to “lazy reviewers” who rely on AI to review the papers.

The Premier League just signed a five-year deal with Microsoft to bring AI to the pitch (digitally, at least). The star player is a new Premier League Companion powered by Azure OpenAI, giving fans personalized insights from 30 seasons of stats, 300k articles, and 9k videos. It’s live now in the League’s revamped app and website, with features like multilingual Q&A and AI-powered fantasy football picks rolling out soon. Let’s just hope the AI doesn’t channel Ted Lasso and start giving pep talks in a Kansas accent.

Microsoft’s Copilot is falling behind in the AI chatbot race, with 20 million weekly users compared to ChatGPT’s 800 million and $10B in annual recurring revenue. Although Copilot has been rolled out to 70% of Fortune 500 companies, only 16% have fully adopted it, citing high costs and implementation challenges. Meanwhile, OpenAI and Anthropic are scaling rapidly, with Claude recently hitting $4B in ARR. Microsoft’s decision to keep Copilot revenue under wraps only further deepens the mystery of how well it’s really doing.

A new Stanford study surveyed 1,500 U.S. workers and 52 AI experts to see where AI should, and shouldn’t, be used in the workplace. While companies rush to automate, the research found a big disconnect between what’s technically possible and what employees actually want.

They broke AI use cases into four zones, and surprisingly, 41% of tasks fell into the “we’re not asking for AI here” or “AI can’t handle this yet” categories, highlighting just how off-target AI efforts can be.

AI as a partner: 81% prefer AI with human oversight or equal collaboration, not full automation.

Help automating the boring stuff: Tasks like scheduling and data cleanup are where workers welcome AI the most.

No creative and client work: Employees reportedly don’t trust AI with external communication or creative output.

Another key finding was that as AI takes over analytical tasks, human-centered abilities like communication and training become more valuable. The chart above highlights that even high-paying roles like “Analyzing data or information” have only a medium human agency score, making them more vulnerable to being handed off to AI.