ChatGPT創始人 轉戰Meta
最近幾周，祖克伯砸重金直接向OpenAI、蘋果、谷歌與Anthropic等競爭對手撬牆角，以強化他在6月成立的「超級智慧實驗室」陣容。在祖克伯6月的備忘錄中，曾看到趙晟佳名字與其他新員工列在一起，不過祖克伯25日強調，趙晟佳是實驗室的聯合創始人，「從第一天起就是我們的首席科學家」。趙晟佳將直接與祖克伯以及Scale AI前執行長、現任Meta「超級智慧實驗室」負責人汪滔（Alexandr Wang）合作。
畢業於中國清華大學的趙晟佳，在史丹佛大學取得電腦科學博士學位。他在OpenAI期間曾參與多項核心專案的研發，像是共同創建ChatGPT，以及協助發展OpenAI的GPT-4、迷你模型、4.1 和o3，先前還領導過OpenAI的合成數據工作。
至於Meta內部另一位資深AI研究員、曾是2018年圖靈獎得主的楊立昆，則繼續擔任基礎AI研究團隊FAIR的首席科學家，他同樣向汪滔報告。
根據媒體取得最新一份名單顯示，目前Meta實驗室的44名員工當中，有50％是來自中國，其中有高達四成曾在OpenAI任職。
此外由OpenAI前成員創立的AI新創公司Anthropic，目前正與投資者進行融資談判的初步階段。部分投資者表示，有興趣將Anthropic的估值定在1,500億美元以上，較其目前615億美元的估值增加一倍多。消息人士透露，這家新創企業已與多家大型中東投資機構接觸，阿布達比AI投資基金MGX也對加入新一輪融資表達興趣。
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全台73個行政區 房價年漲逾一成
遠端商機＋蘋果訂單 創惟11月自結獲利 年增226％
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Forbes
an hour ago
- Forbes
OpenAI: ChatGPT Wants Legal Rights. You Need The Right To Be Forgotten.
As systems like ChatGPT move toward achieving legal privilege, the boundaries between identity, ... More memory, and control are being redefined, often without consent. When OpenAI CEO Sam Altman recently stated that conversations with ChatGPT should one day enjoy legal privilege, similar to those between a patient and a doctor or a client and a lawyer, he wasn't just referring to privacy. He was pointing toward a redefinition of the relationship between people and machines. Legal privilege protects the confidentiality of certain relationships. What's said between a patient and physician, or a client and attorney, is shielded from subpoenas, court disclosures, and adversarial scrutiny. Extending that same protection to AI interactions means treating the machine not as a tool, but as a participant in a privileged exchange. This is more than a policy suggestion. It's a legal and philosophical shift with consequences no one has fully reckoned with. It also comes at a time when the legal system is already being tested. In The New York Times' lawsuit against OpenAI, the paper has asked courts to compel the company to preserve all user prompts, including those the company says are deleted after 30 days. That request is under appeal. Meanwhile, Altman's suggestion that AI chats deserve legal shielding raises the question: if they're protected like therapy sessions, what does that make the system listening on the other side? People are already treating AI like a confidant. According to Common Sense Media, three in four teens have used an AI chatbot, and over half say they trust the advice they receive at least somewhat. Many describe a growing reliance on these systems to process everything from school to relationships. Altman himself has called this emotional over-reliance 'really bad and dangerous.' But it's not just teens. AI is being integrated into therapeutic apps, career coaching tools, HR systems, and even spiritual guidance platforms. In some healthcare environments, AI is being used to draft communications and interpret lab data before a doctor even sees it. These systems are present in decision-making loops, and their presence is being normalized. This is how it begins. First, protect the conversation. Then, protect the system. What starts as a conversation about privacy quickly evolves into a framework centered on rights, autonomy, and standing. We've seen this play out before. In U.S. law, corporations were gradually granted legal personhood, not because they were considered people, but because they acted as consistent legal entities that required protection and responsibility under the law. Over time, personhood became a useful legal fiction. Something similar may now be unfolding with AI—not because it is sentient, but because it interacts with humans in ways that mimic protected relationships. The law adapts to behavior, not just biology. The Legal System Isn't Ready For What ChatGPT Is Proposing There is no global consensus on how to regulate AI memory, consent, or interaction logs. The EU's AI Act introduces transparency mandates, but memory rights are still undefined. In the U.S., state-level data laws conflict, and no federal policy yet addresses what it means to interact with a memory‑enabled AI. (See my recent Forbes piece on why AI regulation is effectively dead—and what businesses need to do instead.) The physical location of a server is not just a technical detail. It's a legal trigger. A conversation stored on a server in California is subject to U.S. law. If it's routed through Frankfurt, it becomes subject to GDPR. When AI systems retain memory, context, and inferred consent, the server location effectively defines sovereignty over the interaction. That has implications for litigation, subpoenas, discovery, and privacy. 'I almost wish they'd go ahead and grant these AI systems legal personhood, as if they were therapists or clergy,' says technology attorney John Kheit. 'Because if they are, then all this passive data collection starts to look a lot like an illegal wiretap, which would thereby give humans privacy rights/protections when interacting with AI. It would also, then, require AI providers to disclose 'other parties to the conversation', i.e., that the provider is a mining party reading the data, and if advertisers are getting at the private conversations.' Infrastructure choices are now geopolitical. They determine how AI systems behave under pressure and what recourse a user has when something goes wrong. And yet, underneath all of this is a deeper motive: monetization. But they won't be the only ones asking questions. Every conversation becomes a four-party exchange: the user, the model, the platform's internal optimization engine, and the advertiser paying for access. It's entirely plausible for a prompt about the Pittsburgh Steelers to return a response that subtly inserts 'Buy Coke' mid-paragraph. Not because it's relevant—but because it's profitable. Recent research shows users are significantly worse at detecting unlabeled advertising when it's embedded inside AI-generated content. Worse, these ads are initially rated as more trustworthy until users discover they are, in fact, ads. At that point, they're also rated as more manipulative. 'In experiential marketing, trust is everything,' says Jeff Boedges, Founder of Soho Experiential. 'You can't fake a relationship, and you can't exploit it without consequence. If AI systems are going to remember us, recommend things to us, or even influence us, we'd better know exactly what they remember and why. Otherwise, it's not personalization. It's manipulation.' Now consider what happens when advertisers gain access to psychographic modeling: 'Which users are most emotionally vulnerable to this type of message?' becomes a viable, queryable prompt. And AI systems don't need to hand over spreadsheets to be valuable. With retrieval-augmented generation (RAG) and reinforcement learning from human feedback (RLHF), the model can shape language in real time based on prior sentiment, clickstream data, and fine-tuned advertiser objectives. This isn't hypothetical—it's how modern adtech already works. At that point, the chatbot isn't a chatbot. It's a simulation environment for influence. It is trained to build trust, then designed to monetize it. Your behavioral patterns become the product. Your emotional response becomes the target for optimization. The business model is clear: black-boxed behavioral insight at scale, delivered through helpful design, hidden from oversight, and nearly impossible to detect. We are entering a phase where machines will be granted protections without personhood, and influence without responsibility. If a user confesses to a crime during a legally privileged AI session, is the platform compelled to report it or remain silent? And who makes that decision? These are not edge cases. They are coming quickly. And they are coming at scale. Why ChatGPT Must Remain A Model—and Why Humans Must Regain Consent As generative AI systems evolve into persistent, adaptive participants in daily life, it becomes more important than ever to reassert a boundary: models must remain models. They cannot assume the legal, ethical, or sovereign status of a person quietly. And the humans generating the data that train these systems must retain explicit rights over their contributions. What we need is a standardized, enforceable system of data contracting, one that allows individuals to knowingly, transparently, and voluntarily contribute data for a limited, mutually agreed-upon window of use. This contract must be clear on scope, duration, value exchange, and termination. And it must treat data ownership as immutable, even during active use. That means: When a contract ends, or if a company violates its terms, the individual's data must, by law, be erased from the model, its training set, and any derivative products. 'Right to be forgotten' must mean what it says. But to be credible, this system must work both ways: This isn't just about ethics. It's about enforceable, mutual accountability. The user experience must be seamless and scalable. The legal backend must be secure. And the result should be a new economic compact—where humans know when they're participating in AI development, and models are kept in their place. ChatGPT Is Changing the Risk Surface. Here's How to Respond. The shift toward AI systems as quasi-participants—not just tools—will reshape legal exposure, data governance, product liability, and customer trust. Whether you're building AI, integrating it into your workflows, or using it to interface with customers, here are five things you should be doing immediately: ChatGPT May Get Privilege. You Should Get the Right to Be Forgotten. This moment isn't just about what AI can do. It's about what your business is letting it do, what it remembers, and who gets access to that memory. Ignore that, and you're not just risking privacy violations, you're risking long-term brand trust and regulatory blowback. At the very least, we need a legal framework that defines how AI memory is governed. Not as a priest, not as a doctor, and not as a partner, but perhaps as a witness. Something that stores information and can be examined when context demands it, with clear boundaries on access, deletion, and use. The public conversation remains focused on privacy. But the fundamental shift is about control. And unless the legal and regulatory frameworks evolve rapidly, the terms of engagement will be set, not by policy or users, but by whoever owns the box. Which is why, in the age of AI, the right to be forgotten may become the most valuable human right we have. Not just because your data could be used against you—but because your identity itself can now be captured, modeled, and monetized in ways that persist beyond your control. Your patterns, preferences, emotional triggers, and psychological fingerprints don't disappear when the session ends. They live on inside a system that never forgets, never sleeps, and never stops optimizing. Without the ability to revoke access to your data, you don't just lose privacy. You lose leverage. You lose the ability to opt out of prediction. You lose control over how you're remembered, represented, and replicated. The right to be forgotten isn't about hiding. It's about sovereignty. And in a world where AI systems like ChatGPT will increasingly shape our choices, our identities, and our outcomes, the ability to walk away may be the last form of freedom that still belongs to you.
Yahoo
an hour ago
- Yahoo
Broadcom is no longer the 'poor man's Nvidia' in the AI race
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Yahoo
an hour ago
- Yahoo
1 Super Artificial Intelligence (AI) Stock Billionaire Bill Gates Has 25% of His Foundation's Portfolio Invested In
Key Points The Gates Foundation holds a substantial number of Microsoft shares. Microsoft has become a top player in offering artificial intelligence models. However, the stock is starting to appear somewhat pricey compared to its peers. 10 stocks we like better than Microsoft › Bill Gates is a well-known entrepreneur, having co-founded Microsoft (NASDAQ: MSFT) in the mid-1970s. This made him a fortune, and he constantly ranks among the richest people in the world. He established the Gates Foundation Trust, one of the world's most well-funded foundations. By examining its holdings, investors can gain insight into what one of the world's brightest minds considers top stock picks, and they've identified an AI stock that has been a stellar performer in recent years. In fact, the stock has more than doubled since the start of 2023 alone. What is this stock? It's none other than Microsoft. Microsoft is the foundation's top holding This really shouldn't come as a surprise to anyone. Bill Gates runs the fund, so he will fill it with a company that he thinks will succeed. Most of this stock was donated from Gates' wealth; however, if the foundation didn't think Microsoft was set to succeed, they would have sold it a long time ago and moved on to something else. About 25% of the foundation's worth is tied up in Microsoft stock, valued at around $10.7 billion. That's a concentrated bet for a charitable foundation, but it has worked out well with Microsoft's recent success. Microsoft has emerged as a top AI pick due to its role as a facilitator in the space. It isn't developing its own generative AI model; instead, it's offering many of the leading ones on its cloud computing platform, Azure. Developers can choose from OpenAI's ChatGPT, a leading option, Meta Platforms' Llama, DeepSeek's R1 (a more affordable alternative from China), or xAI's Grok, a company founded by Elon Musk. By offering a wide range of generative AI models, Microsoft isn't locking its clients into a single provider. This has made Azure a top choice for building AI models on, which is why it has outgrown its peers in recent quarters. We'll get an update on how the other cloud computing providers -- namely Alphabet's Google Cloud and Amazon's Amazon Web Services (AWS) -- in the next few weeks, but I'd be shocked if Azure isn't growing quicker than they are. Azure has become a top platform for building AI applications, but has it done enough to make Microsoft a top buy now? Microsoft's stock is starting to look a bit pricey for its growth If Microsoft derived all of its revenue from Azure, I'd be a buyer at nearly any price. However, Microsoft has other product lines that aren't growing as quickly, which slows the company's overall growth pace. In its latest period -- the third quarter of fiscal 2025 -- overall revenue rose to $70.1 billion at a 13% pace. While Microsoft doesn't break out the revenue generated by Azure, we know from prior information that it accounts for over half of the Intelligent Cloud division, which brought in $26.8 billion during Q3 (ending March 31). They do provide Azure's growth rate, which was Microsoft's top-performing division in Q3, rising 33% year over year. Microsoft's diluted earnings per share also rose an impressive 18%, but is that fast enough to justify its valuation? Microsoft trades at nearly 40 times trailing earnings, which is a very expensive price tag and exceeds its recent highs reached during the AI arms race period. Wall Street analysts project $15.14 in earnings per share for fiscal 2026 (ending June 30, 2026), which indicates the stock trades at 33.7 times forward earnings. That's still a high valuation, and investors need to start being a bit cautious when stocks reach that level, especially when they're growing at Microsoft's pace. Yes, Microsoft is growing faster than the market, but it's not growing as fast as some of its peers. Take Meta Platforms, for example. It trades at 28 times trailing earnings and grew revenue at a 16% pace during its last quarter with 36% earnings-per-share growth. That's a cheaper stock growing faster, which should cause Microsoft investors to question whether it's the best big tech stock to be in right now. Numerous other big tech stocks have better growth numbers and cheaper valuations than Microsoft. Although it's a dominant company, it's starting to look a bit expensive compared to its peers. Should you buy stock in Microsoft right now? Before you buy stock in Microsoft, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and Microsoft wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $636,628!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $1,063,471!* Now, it's worth noting Stock Advisor's total average return is 1,041% — a market-crushing outperformance compared to 183% for the S&P 500. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of July 21, 2025 Keithen Drury has positions in Alphabet, Amazon, and Meta Platforms. The Motley Fool has positions in and recommends Alphabet, Amazon, Meta Platforms, and Microsoft. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy. 1 Super Artificial Intelligence (AI) Stock Billionaire Bill Gates Has 25% of His Foundation's Portfolio Invested In was originally published by The Motley Fool Sign in to access your portfolio
