Meta, Microsoft Fall
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Meta Platforms reported mixed third-quarter earnings results Wednesday afternoon. Its shares were down over 11% by midmorning Thursday.Earnings-per-share were $1.05, well behind Wall Street’s consensus estimate of $6.
Your Meta -owned feeds — Instagram and Facebook, notably — may soon feature even more content generated by artificial intelligence. Meta CEO Mark Zuckerberg himself said that was the plan. Zuckerberg made the declaration during an earnings call this week. He talked about AI being the next big change in what appears on your social feeds.
14hon MSN
Meta forecasts bigger capital costs next year as Zuckerberg lays out aggressive AI buildout
On Wednesday, Alphabet and Microsoft also signaled higher AI investments. OpenAI CEO Sam Altman on Tuesday said he would eventually like the company to be able to add 1 gigawatt of compute every week - an astronomical sum given that each gigawatt currently comes with a capital cost of more than $40 billion.
It's all too easy to make AI content, and Meta's recommendation systems will deliver that content to users. Soon enough, it may be nearly impossible to tell whether the videos in our feeds are real or AI.
Meta has laid off 600 employees in its AI unit as it restructures operations and consolidates leadership under Wang Jian to advance its AI strategy.
U.S. Federal Reserve Chairman Jerome Powell bifurcated the stock market yesterday when he delivered a 0.25% rate cut that the market was expecting and then, unexpectedly, said he did not believe that the AI sector was in a bubble akin to the dotcom boom of 2000.
The Facebook parent’s business model sparks more questions about the eventual payoff than rivals such as Google and Microsoft.
Meta plans to spend up to $72 billion on AI infrastructure this year, with CEO Mark Zuckerberg defending the long-term strategy.
The move comes after Strike 3 Holdings discovered illegal downloads of some of its adult films on Meta corporate IP addresses, as well as other downloads that Meta allegedly concealed using a “stealth network” of 2,
The proof-of-concept could pave the way for a new class of AI debuggers, making language models more reliable for business-critical applications.