Meta’s Ambitious Plan for Artificial General Intelligence
Opinion Meta's CEO has ambitious goals for artificial general intelligence, a technology that is both thrilling and frightening -- yet still largely untested.
Mark Zuckerberg’s AI Bet A Real Long Shot Dream
🌟 Meta Chief Executive Mark Zuckerberg, who runs one of the biggest AI research efforts around, wants to run one that’s even bigger. It’s a pretty far-out idea. On Thursday, he said that Meta is leveling up its work to tackle not just artificial intelligence, but also what’s known as artificial general intelligence (AGI). 🚀
AI and AGI are already very nebulous terms, but in a nutshell, with “general intelligence” systems Zuckerberg wants to create much, much smarter computing systems — ones that at least match human cognitive abilities like learning, reasoning, planning, creating, and remembering information.
Meta’s Quest for Super Intelligence
That’s a sensible goal for a tech giant eager to shape the future of computing, attract the best research talent, and keep antsy shareholders happy. But for you and me, it’s not likely to mean a hyperintelligent bot will be offering advice through your smart glasses anytime soon. 😅
That’s because today’s AI, while exciting to computer scientists and much of the general public, hasn’t really delivered a revolution yet. It still struggles to distinguish hard facts from flights of fancy. Even so, it’s still miles ahead of AGI, which exists mostly as a domain of research and speculation. But it’s Zuckerberg’s aspiration.
“It’s become clear that the next generation of services requires building full general intelligence,” Zuckerberg said in a post on Meta’s Threads social network. “Building the best AI assistants — AIs for creators, AIs for businesses and more — needs advances in every area of AI from reasoning to planning to coding to memory and other cognitive abilities.”
And he’s serious about it, saying that by year’s end, Meta will have 350,000 top-end Nvidia GPUs — the top-tier AI processors, which cost in the neighborhood of $30,000 apiece. Adding in other GPUs, that’ll bring processing power equivalent to 600,000 H100s, Zuckerberg said, dangling a big carrot in front of AI researchers’ eyes. 😲
Giving a plug for his effort to usher in a metaverse that blends computer-generated and real worlds, he said that wearable devices like Meta’s Ray-Ban smart glasses could be an ideal interface for letting AI see what you see and helping you navigate reality.
Today’s AI, best exemplified by large language models (LLMs) like OpenAI’s GPT, Google’s Gemini, Anthropic’s Claude, and Facebook’s Llama, spot relationships among words in vast tracts of text on the internet, like forum posts, books, and news articles. The result is a generative AI that can generate answers to many questions, restyle your job application answers to sound more formal, and more. But while LLM responses often sound plausible, these AI systems don’t truly know anything.
What Exactly Is Artificial General Intelligence?
AGI, in contrast, is more like your brain, generally speaking. And with steady computing progress, there’s a likelihood that if AGI ever is achieved, it will lead to superhuman intelligence afterward.
In an interview with The ENBLE, Zuckerberg didn’t offer any quick AGI definition. “You can quibble about if general intelligence is akin to human level intelligence, or is it like human-plus, or is it some far-future superintelligence,” he said. “But to me, the important part is actually the breadth of it, which is that intelligence has all these different capabilities where you have to be able to reason and have intuition.”
OpenAI and Google’s DeepMind are among those pursuing AGI. Zuckerberg hopes Meta will be the company that delivers it.
To make that happen, he’s merged the company’s two AI research teams, the older-school FAIR effort and the newer generative AI team that builds Llama.
How Close Are We to Achieving AGI?
Opinions vary on whether today’s LLMs, which leaped into mainstream awareness with the arrival of OpenAI’s ChatGPT service based on its GPT model, are a step toward AGI. Microsoft researchers, in a 2023 paper, concluded they are.
“Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence system,” the researchers concluded.
There are plenty of skeptics, though, including critics like the University of Washington’s Emily Bender who deride LLMs as mere “stochastic parrots” that regurgitate information somewhat randomly based on statistical patterns in their training data.
Others, including Facebook researcher and AI pioneer Yann LeCun, have argued that a sufficiently sophisticated training process effectively can build a representation of the real world into an AI model. Indeed, some remarkable abilities emerged from LLMs trained on text.
Researchers now are trying to advance AI with richer training data, a direction leading toward a “world model” that captures our environment in much more depth.
LLMs are trained on text, but Google’s Gemini and other new “multimodal” AI models are trained also on video, photos, audio, and other source data. Tesla CEO Elon Musk believes his company’s humanoid robots will gather useful video training data as they navigate the real world.
But richer training data gets you only so far if the same basic problems afflict AIs, like producing actions based on interpretations of a situation that is statistically plausible but not actually correct. Many researchers believe just goosing today’s AI will be insufficient to reach AGI.
And then there’s the thorny question of whether it’s even a good idea. Regulators, ethicists, and computer scientists are debating the issue, but it’s a highly speculative area, and there’s no consensus about how to control AGI-endowed machines or how to at least align them with humanity’s welfare.
Zuckerberg insists Meta’s AI effort is proceeding cautiously, including with the Llama 3 LLM it’s now begun training. “We’ve got an exciting roadmap of future models that we’re going to keep training responsibly and safely, too,” he said.
That’s nice to hear, given AI’s potential power and importance. Judging by how much difficulty humanity has had with privacy erosion, social media disinformation, identity theft, and other technological problems, perhaps we should be grateful Zuckerberg has given us at least a few years’ warning about Meta’s AGI plans.
🤔 Quick Q&A Session
Q: How close are we to achieving AGI?
Opinions vary, but some researchers believe that large language models (LLMs) like GPT-4 could be viewed as early versions of AGI systems. However, critics argue that LLMs are like “stochastic parrots” that simply regurgitate information without truly understanding it. Achieving AGI will require more than just advancing current AI systems.
Q: What is the difference between AI and AGI?
AI refers to artificial intelligence systems that can perform specific tasks, while AGI aims to create computing systems that possess general intelligence, similar to human cognitive abilities such as learning, reasoning, planning, creating, and remembering.
Q: What are the challenges in developing AGI?
Developing AGI poses challenges in terms of defining its capabilities, aligning it with human values, and ensuring its safe and responsible deployment. There’s ongoing debate among regulators, ethicists, and computer scientists regarding these issues.
Q: How is Meta contributing to AGI research?
Meta, led by Mark Zuckerberg, has merged its AI research teams and is investing in top-tier AI processors to advance its AGI efforts. They are also exploring the use of wearable devices like Ray-Ban smart glasses as interfaces for AI systems.
Future Developments and Impact
The pursuit of AGI is an ambitious endeavor that could have significant implications for the future of computing and humanity as a whole. If successful, AGI could lead to computing systems with superhuman intelligence and capabilities. However, there are still many challenges to overcome, both technically and ethically.
As research and development in AI and AGI continue, it’s important to consider the potential impact and consequences. Ensuring the responsible and safe development of AGI, aligned with human values and welfare, is crucial. It requires collaboration among researchers, industry leaders, policymakers, and society at large.
While the vision of AGI may seem fantastical, it’s through bold aspirations and efforts that technological breakthroughs can be made. Meta’s commitment to advancing AI and striving for AGI pushes the boundaries of what is possible and drives innovation in the field.
📚 Reference List
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💡 Want to learn more about the future of AI and AGI? Check out these insightful articles! Share them with your friends and spark a conversation! Let’s explore the exciting possibilities together. 😄
Article originally published on ENBLE. This article was created with the assistance of an AI engine.
