Meta's Superintelligence Lab unveils its first public model, Muse Spark

Meta's AI advancements could redefine app economics, enhancing user experiences and solidifying its competitive edge in the tech industry. The post Meta debuts Muse Spark, its first major AI model since rebuilding its AI lab appeared first on Crypto Briefing.

The post Analyst issues new Meta stock price target after ‘deeply undervalued’ call appeared on BitcoinEthereumNews.com. Meta Platforms (NASDAQ: META) has received a fresh bullish endorsement on Wall Street after Truist Securities reaffirmed its ‘Buy’ rating and maintained an $840 stock price target. The target implies upside of about 37% from Meta’s press-time price of $612. META one-week stock price chart. Source: Finbold The updated outlook comes as the firm argued that Meta remains deeply undervalued, citing the company’s massive global user base and growing ability to monetize artificial intelligence across its ecosystem. Truist analyst Youssef Squali’s thesis centers on Meta’s unique distribution advantage, which includes more than 3.5 billion daily users, over 200 million small and medium-sized businesses, and more than 10 million advertisers across its platforms. According to the research note, Meta’s AI strategy is increasingly focused on monetization rather than solely compet

Net-zero pledges of Google and Amazon slip out of reach, and struggling Meta makes frantic moves Hello, and welcome to TechScape. I’m your host, Blake Montgomery, the Guardian’s US tech editor, writing to you after a rodeo in rural Texas, where I celebrated Independence Day. Today in tech, we’re discussing how tech giants’ investments in AI are hindering their pledges of climate neutrality, Meta’s frantic search for new lines of business, and Americans’ anger at tech’s political influence. Revealed: landmark Scottish AI project has no prospect of meeting renewables promise US residents angry at datacenters ‘being shoved down our throats’ are recalling officials Americans disgusted at Trump earning $1bn from crypto as president: ‘Obviously a grift’ Tesla sales surpass expectations for second quarter as Musk backlash seems to cool 3,000% bonuses but a growing wealth divide: South Korea grapples with its AI chip boom China wants to solve the hardest problem in robotics – making hands What

With the rapid progress of AI capabilities and the move to agentic systems, organizations are expanding their use cases as the technology continues to grow. That constant evolution also introduces risk, leaving IT leaders to wonder which investments will prove valuable even six months into the future. Returning to the foundational elements of AI architecture—the…

Salesforce's European AI expansion could redefine enterprise tech, raising critical issues around data ownership and transparency in AI systems. The post Salesforce pours billions into European AI expansion as agentic systems reshape enterprise tech appeared first on Crypto Briefing.

The legal actions against Meta could reshape tech industry standards, impacting user engagement strategies and potentially reducing ad revenues. The post US states seek $1.4T in penalties from Meta over addiction claims appeared first on Crypto Briefing.

Application programming interfaces have been successful because they define the limits of permissible exchange, including who may take what action, when, and under what circumstances. Those limitations create a framework for understanding the behavior of distributed systems. And they make it possible to enforce policy at the boundary between interacting systems. What constrains distributed systems isn’t access, but execution. With autonomous data movement and action occurring at machine speeds, where processes unfold sequentially over time rather than as a singular event, APIs no longer provide a sufficient means of enforcing boundaries. The problem is no longer whether a request is valid. It is whether a sequence of actions remains safe. For agentic systems, there needs to be runtime guardrails around what they can read, write, and execute. Microsegmentation, enforced through network and kernel-level policies, defines those guardrails. APIs made systems predictable APIs were successfu

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