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专注于电动车和能源领域的播客主持人和内容创作者。
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Jensen Huang: 英伟达CEO杰森黄在CES主题演讲中宣告了AI代理时代的到来。他认为AI代理是新的劳动力,每个公司的IT部门未来都将成为AI代理的HR部门。他还强调,英伟达的AI芯片改进速度远超摩尔定律,通过在架构、芯片、系统、库和算法上的同时创新实现。推动推理性能的提升将降低推理成本,这对于难以实现盈利的AI行业至关重要。最后,他表示将AI超级计算机放置在每个数据科学家、AI研究人员和学生面前,能够让他们参与并塑造AI时代。 Rev Liberadian: 英伟达Omniverse和模拟技术副总裁Rev Liberadian指出,英伟达的目标是使AI代理真正发挥作用,并尽可能快速部署。 主持人: 本期节目讨论了AI代理时代的到来,以及英伟达在这一领域的战略布局。英伟达正在进军AI的各个垂直领域,包括机器人、自动驾驶、代理、消费设备等等。英伟达CEO宣告AI代理时代已经到来,AI领域正进入一个陡峭的指数级增长曲线。英伟达的战略是使AI在生活的各个方面都尽可能地无摩擦部署,从而极大地提高对AI芯片的需求。英伟达正在效仿谷歌早期的策略,从单一业务转向覆盖尽可能多的相关垂直领域。 Jensen Huang: 英伟达首席执行官杰森·黄在拉斯维加斯举行的CES主题演讲中宣布,人工智能代理时代已经到来。他展示了一张图表,展示了人工智能从感知人工智能、生成式人工智能到代理式人工智能,再到物理人工智能的演变过程。他认为,代理式人工智能将成为新的劳动力,并预测每个公司的IT部门都将成为人工智能代理的HR部门。他还强调了英伟达人工智能芯片的快速发展速度,其速度远远超过摩尔定律。他解释说,这是因为英伟达能够同时创新整个技术栈,包括架构、芯片、系统、库和算法。他认为,提高推理性能将降低推理成本,这对难以实现盈利的AI行业至关重要。他还宣布了英伟达的Nemotron模型家族,这是一个具有三种不同尺寸的模型系列,可以满足从边缘设备推理到需要前沿模型的任务等各种用例。这些模型将以文本和视觉两种形式提供,并基于Meta的Llama模型进行微调,并完全开源。他还展示了Project Digits,这是一款小巧的AI工作站,其尺寸与Mac Mini或一本精装书差不多大,但它包含了英伟达的Grace Hopper超级芯片,能够提供高达每秒一千万亿次浮点运算的AI计算能力。这使得数据科学家、AI研究人员和学生能够在自己的桌面上运行大型AI模型。 Rev Liberadian: 英伟达Omniverse和模拟技术副总裁Rev Liberadian解释了英伟达为AI编排创建的蓝图,这些蓝图旨在指导代理完成特定任务,并帮助协调多个代理。这些蓝图与Langchain、Llama Index和Daily等AI编排公司合作创建,并将在英伟达的企业平台上提供。他给出了几个例子,例如一个处理代码文档以确保存储库易于导航的蓝图,以及一个生成类似于谷歌Notebook LM结果的PDF到播客的蓝图。他还展示了一个允许代理分析视频的蓝图,该蓝图集成了多个服务,可以比实时观看快30倍地提供高质量的视频分析。这在更新系统和设计新流程方面具有巨大的应用价值,例如监控工业流程。 主持人:总结了英伟达在CES上发布的各种产品和服务,包括面向游戏、汽车和消费者的产品。他指出,英伟达的目标是使AI部署在生活的各个方面都尽可能地无摩擦,从而推动对AI芯片的需求。

Deep Dive

Key Insights

What is the significance of NVIDIA's announcement of the Nemotron model family?

NVIDIA's Nemotron model family represents a significant step in democratizing AI development by offering models in three sizes for various use cases, from edge device inference to frontier model tasks. These models are fully open-sourced, with text-based models fine-tuned from Meta's LLaMA, enabling competition on price and accessibility across agentic AI applications.

Why is NVIDIA's Project Digits workstation considered a game-changer?

Project Digits is a compact AI workstation that delivers a petaflop of AI compute, capable of running inference for models up to 200 billion parameters. Priced at $3,000, it makes high-performance AI prototyping and fine-tuning accessible to data scientists, researchers, and students, effectively placing an AI supercomputer on their desks.

How does NVIDIA's approach to AI orchestration differ from competitors?

NVIDIA has released blueprints for AI orchestration, designed to guide agents through specific tasks and coordinate multiple agents. These blueprints, developed in partnership with companies like Langchain and Llama Index, aim to make agent deployment faster and more efficient, addressing complex workflows such as code documentation and video analysis.

What are the key applications of NVIDIA's video analysis blueprint?

NVIDIA's video analysis blueprint enables high-quality video analysis 30 times faster than real-time, with applications in industrial process monitoring and defect detection. With over 1.5 billion enterprise cameras globally recording 7 trillion hours of video annually, this technology can significantly reduce losses from undetected defects and improve operational efficiency.

How does NVIDIA's strategy reflect a shift from being a chipmaker to an AI-first tech giant?

NVIDIA is expanding beyond chip manufacturing by offering a comprehensive ecosystem for AI development, including agent models, orchestration tools, and hardware like Project Digits. This shift aims to make AI deployment frictionless across industries, driving demand for NVIDIA's AI chips while positioning the company as a leader in AI innovation.

What is the significance of Anthropic's $60 billion valuation?

Anthropic's $60 billion valuation, up from $18 billion, reflects investor confidence in its enterprise market share growth and potential to compete with OpenAI. Despite trailing OpenAI in revenue ($875 million vs. $3.7 billion), Anthropic's focus on enterprise adoption and future model advancements has driven its valuation surge.

Why is the U.S. government's stance on AI infrastructure investments in the Middle East significant?

The U.S. government's comfort level with AI infrastructure investments in the Middle East is crucial due to the region's strategic position between the U.S. and China. Investments like Microsoft's in G42 highlight geopolitical tensions, while deals like the $20 billion data center investment by an Emirati billionaire in the U.S. underscore the importance of private sector-led infrastructure development.

What are the implications of Microsoft's $3 billion investment in AI infrastructure in India?

Microsoft's $3 billion investment in AI infrastructure in India, coupled with plans to train 10 million people in AI, aims to accelerate AI adoption and skill development in the country. This aligns with India's growing role as a hub for AI innovation and reinforces Microsoft's commitment to global AI diffusion.

How does NVIDIA's AI chip performance compare to Moore's Law?

NVIDIA's AI chips are improving 30 times faster than Moore's Law, driven by innovations across architecture, chip design, system integration, and algorithms. This rapid advancement is critical for reducing inference costs and enabling broader AI adoption across industries.

What is the potential impact of NVIDIA's open-source approach on the AI industry?

NVIDIA's open-source approach, exemplified by the Nemotron model family, is likely to accelerate the commoditization of AI models. By offering competitive pricing and accessibility, NVIDIA is driving a price war among AI labs, making advanced AI tools more widely available and fostering innovation across the industry.

Chapters
Anthropic secures a massive $2 billion funding round at a $60 billion valuation, continuing the trend of mega-financing in the AI sector. Its revenue is significantly lower than OpenAI’s, but investors seem to be betting on its growth trajectory, particularly in enterprise sales. The discussion also touches upon the potential of Anthropic releasing new models and the implications for OpenAI's valuation.
  • Anthropic raises $2 billion at a $60 billion valuation.
  • Anthropic's revenue is significantly lower than OpenAI's.
  • Investors are betting on Anthropic's growth trajectory in the enterprise market.

Shownotes Transcript

Translations:
中文

On today's AI Daily Brief, NVIDIA's CEO declares the age of AI agentics is here at CES. And before that, in the headlines, Anthropic is raising new money at a $60 billion valuation. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. To join the conversation, follow the Discord link in our show notes.

Welcome back to the AI Daily Brief Headlines Edition, all the daily AI news you need in around five minutes. To the surprise of no one, the trend of mega financing rounds for AI companies appears to be continuing into 2025, with the latest round coming together seemingly for Anthropic.

According to people familiar with the investment round, say that the company is talking about raising about $2 billion at a $60 billion valuation. The round appears to be being led by Lightspeed Ventures and represents a big jump in its valuation. The company's last price round was at $18 billion and was led by Menlo Ventures. Basically, ever since OpenAI raised its mega round in October that valued it at $157 billion, it's been open season for fundraising for these huge foundation model firms.

Originally, we had seen numbers in the $40 to $50 billion range for Anthropic, but then Elon's XAI raised it around that valuation. And I kind of assumed that just based on market forces, Anthropic might get a bump from that.

Sure enough, that seems to be the case. Anthropix revenue is definitely behind OpenAI's. OpenAI is looking at something like $3.7 billion, while sources suggest that Anthropix annualized revenue is around $875 million. One thing that is notable, however, is that Anthropix has significantly increased its market share when it comes to enterprise buying. It definitely appears to be scooping some of that business away from OpenAI, and so perhaps investors are betting on the trajectory rather than the current state.

Of course, the biggest difference between Anthropic and OpenAI is not just their enterprise sales, but the fact that ChatGPT is at this point largely synonymous with AI for consumers, and that shows up in their revenue numbers as well. A lot of the discourse was about what Anthropic is going to use this money for. Chubby writes, I mean, nice and all, but it's about time for Anthropic to release a reasoning model in Opus 3.5 or 4. Sonnet 3.5 is good, no doubt, but OpenAI seems to have a good advantage now.

Think broadly, there's a sense that maybe the next shoe to drop in terms of model updates will be Anthropic, but of course, we'll have to wait and see. Some folks think that this valuation actually makes OpenAI look like an even better investment. Dolly Bolly writes, Anthropic being valued at one third of OpenAI makes OpenAI look like a long. Ultimately, I still think we're in a situation where there are an extremely small number of companies that are legitimate contenders to get to AGI and beyond, and the valuations for that are fairly uncapped because of it.

Next up, another one of the big themes for 2025 is, of course, going to be infrastructure build-out, and that has a significantly geopolitical dimension as well.

One of the big questions is how comfortable the U.S. government is going to be with U.S. companies investing in and partnering in the Middle East. The Gulf states are quite literally between the U.S. and China, having strong trade relationships with both sides. This has been a point of contention, flaring up in places like Microsoft's minority investment in G42. And so it was interesting to see that President-elect Donald Trump has announced the deal going the other way with a Gulf firm spending billions of dollars in the U.S.,

In a press conference at Mar-a-Lago yesterday, property development mogul Hassan Sajwani said, It's been amazing news for me and my family when Trump was elected in November. We've been waiting four years to increase our investment in the U.S. to very large amounts of money.

According to the announcement, Sajwani is planning to invest $20 billion to build new data centers across the U.S., and Trump said that he was actually pledging at least that amount, saying, quote, they may go double or even somewhat more than double that amount of money. The first phase of the multistage investment will focus on building facilities in Arizona, Illinois, Indiana, Louisiana, Michigan, Ohio, Oklahoma, and Texas.

Now, for a sense of scale, Microsoft intends to spend about $80 billion on AI data centers this year, with half of that being deployed in the U.S. This deal seems to be somewhat emblematic of the way Trump intends to approach AI infrastructure policy. One of the ideas that has percolated from Trump's social media account was a proclamation that anyone investing a billion dollars in the U.S. would be fast-tracked through environmental regulation and permitting. The goal seems to be to put private sector investors in a position to replace and exceed government subsidies through things like the CHIPS Act.

During a recent interview, Sam Altman discussed why this plan could make sense, commenting, There's a real opportunity for the Trump administration to do something much better than the CHIPS Act as a follow-on. I don't think the CHIPS Act has been as effective as any of us hoped. The thing I really deeply agree with President Trump on is, it is wild how difficult it has become to build things in the United States. Power plants, data centers, any of that kind of stuff. I understand how bureaucratic cruft builds up, but it's not helpful to the country in general.

This investment from the Emirati billionaire also echoes calls from Microsoft President Brad Smith. In a blog post published last week, Smith said, the most important U.S. public policy priority should be to ensure that the U.S. private sector can continue to advance with the wind at its back. He also called for a focus on exporting American AI to allies and friends, particularly through partnerships in the Gulf states.

Speaking of infrastructure build-out, two more quick stories before we get out of here. Microsoft intends to invest $3 billion in AI and cloud infrastructure in India over the next two years. CEO Satya Nadella announced the plans at an event in Bengaluru on Tuesday. He said the company will also provide AI training to 10 million people in India. Nadella said, The investments in infrastructure and skilling we are announcing today reaffirm our commitment to make India AI first and will help ensure people and organizations across the country benefit broadly. The diffusion rate of AI in India is exciting.

Amazon Web Services, meanwhile, says it plans to invest at least $11 billion to expand infrastructure in Georgia. In a press release, the company wrote, AWS is proud to expand our operations in Georgia to help drive the next generation of cutting-edge technologies such as AI. The announcement comes just eight months after the company committed $11 billion to building out data centers in Indiana. Interestingly, Georgia is quietly going through an AI infrastructure boom. According to a report from GovTech, data center construction grew by 76% last year in the metro Atlanta area.

I expect that we will hear lots and lots of this type of infrastructure build-out story this year. But for now, that is going to do it for today's AI Daily Brief Headlines Edition. Next up, the main episode. Today's episode is brought to you by Vanta. Whether you're starting or scaling your company's security program, demonstrating top-notch security practices and establishing trust is more important than ever.

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If there is one thing that's clear about AI in 2025, it's that the agents are coming. Vertical agents by industry, horizontal agent platforms, agents per function. If you are running a large enterprise, you will be experimenting with agents next year. And given how new this is, all of us are going to be back in pilot mode.

That's why Superintelligent is offering a new product for the beginning of this year. It's an agent readiness and opportunity audit. Over the course of a couple quick weeks, we dig in with your team to understand what type of agents make sense for you to test, what type of infrastructure support you need to be ready, and to ultimately come away with a set of actionable recommendations that get you prepared to figure out how agents can transform your business.

If you are interested in the agent readiness and opportunity audit, reach out directly to me, nlw at bsuper.ai. Put the word agent in the subject line so I know what you're talking about. And let's have you be a leader in the most dynamic part of the AI market. Welcome back to the AI Daily Brief. This week is the great big CES show over in Las Vegas. It's a chance for particularly consumer tech companies to show off their latest innovations as well as where they're headed.

It's kind of a weird event in the sense that a huge number of people go every year, and there are always some interesting announcements, but it's never really the home base of some world-changing announcement. I don't know why, but it's just not the place that people choose to really make their biggest announcements of the year. Perhaps it's just timing. January is kind of a weird time. Still, this year, the big keynote was from NVIDIA's Jensen Huang, and there was so much announced, it is going to be difficult to get through in a single show.

Still, we are going to try. The TL;DR is that NVIDIA is attacking basically every vertical in AI, including robotics, autonomous driving, agents, consumer devices, and much more.

The announcements were in fact so wide-ranging that at least one publication has called this NVIDIA's Apple moment. Right at the core of Jensen's presentation was this declaration that the age of AI agentics is here. For those of you who are not watching, I've got an image up of this great slide that he had showing an up-and-to-the-right graph that goes through perception AI, degenerative AI, to agentic AI, to physical AI.

Under agentic AI, he references coding assistance, customer service, and patient care. Basically, Jensen described the AI sector as heading into a steep exponential curve as agents come online and provide a stepping stone towards a fully robotic world. Over the shorter term, he said, quote, AI agents are the new workforce. The IT department of every company is going to be the HR department of AI agents in the future.

Jensen also mentioned that NVIDIA's AI chips are improving, quote, way faster than Moore's Law. He said that the current model of chips is 30 times faster than the previous generation, adding, we can build the architecture, the chip, the system, the libraries, and the algorithms all at the same time. If you can do that, then you can move faster than Moore's Law because you can innovate across the entire stack. Explaining why this is so crucial for an AI industry struggling to hit profitability, he said, Moore's Law was so important in the history of computing because it drove down computing costs.

The same thing is going to happen with inference where we drive up the performance and as a result, the cost of inference is going to be less. You might remember our discussion yesterday around how Sam Altman was saying that OpenAI's $200 a month subscription is actually not profitable. The presentation itself got rave reviews.

Salesforce CEO Mark Benioff breathlessly posted, Rarely am I so captivated and inspired by a CEO's keynote that it holds my attention for two hours. But Jensen Huang's indefatigable energy makes him one of the most inspiring and visionary leaders among tenured and authentic CEOs.

His ability to innovate while delivering amazing products I genuinely want to buy is remarkable. A true masterclass in running a great tech company. I was particularly struck by his framing of AI's evolution, from perception to generative to agentic and ultimately to physical. Truly inspiring. Still no less breathtaking was the gigantic range of products and services that NVIDIA announced. And so even though I've just said that in general, CES isn't the place for big announcements, this was truly a full-scale product launch.

Now for our purposes, and given the theme of the presentation, I think the most important products was NVIDIA's first full family of agent models. Called NEMOTRON, these models come in three sizes to cover use cases from edge device inference to tasks that require frontier models. Last year, NVIDIA gave a sneak preview of a 70B version of NEMOTRON, which outperformed the same class of models from OpenAI and Anthropic on agentic tasks. The new family of models will also come in two different varieties.

a text-based model for language tasks, as well as a vision-based model optimized for physical AI projects. The models are impressively fully open sourced, with the text models based on a fine tune of Meta's Lama models. This means that NVIDIA will be competing on price with models that cover the full spectrum of agentic use cases. And as a total aside, we could have a very long conversation here around the commoditization of AI models that feels like it's only going to accelerate in the agentic age. Alongside the model family, NVIDIA also released a set of blueprints for AI orchestration.

These are designed to guide agents through specific tasks and can aid in coordination of multiple agents. NVIDIA has partnered with several AI orchestration companies to build blueprints that will be available on NVIDIA's enterprise platform, including Langchain, Llama Index, and Daily. One example created by Crew.ai handles code documentation to ensure repositories are easy to navigate. Another example is a PDF-to-podcast blueprint that produces results similar to Google's Notebook LM.

Rev Liberadian, VP of Omniverse and Simulation Technology at NVIDIA said, That's a lot of words, but basically the goal here is to make agents actually work and be as quick to deploy as possible.

One of the more impressive blueprints shared allows agents to analyze video. A complex pipeline of integrated services can deliver high-quality video analysis 30 times faster than watching it in real time. This has a huge range of extremely valuable applications, both in updating systems with AI and devising new processes with this novel ability. The low-hanging fruit is monitoring of industrial processes. There's currently more than 1.5 billion enterprise cameras deployed worldwide that record 7 trillion hours of video per year. Only a fraction of that actually gets analyzed.

At the same time, manufacturers lose trillions of dollars annually to product defects that could have been spotted earlier using an AI-enhanced camera. This is just one specific example, but one where you can see the immediate tangible ROI right away.

Another marquee announcement from NVIDIA was a small footprint AI workstation called Project Digits. Around the same profile as a Mac Mini or the size of a hardback book, the device contains the company's Grace Blackwell hardware. Huang said the device, quote, runs the entire NVIDIA stack. All of NVIDIA software run on this. It's a cloud computing platform that sits on your desk. It's even a workstation if you'd like it to be. The device can be used as a standalone computer running NVIDIA's Linux-based OS or plugged into a primary Windows or Mac PC.

It can put out a petaflop of AI compute for prototyping, fine-tuning, and running AI models. NVIDIA claims a single unit can run inference for models up to 200 billion parameters. Not quite enough to run the largest version of Meta's Lama model, but plenty of power to run mid-sized modern LLMs locally. A pair of devices can also be networked to deliver inference for models with up to 405 billion parameters. The device will be available in May at a price point of $3,000, which while making it a prosumer product, certainly doesn't make it inaccessible for people.

Huang said, placing an AI supercomputer on the desks of every data scientist, AI researcher, and student empowers them to engage and shape the age of AI.

NVIDIA also launched a range of AI gaming tools. There was an automated producer agent that can manage live Twitch streams, as well as AI-driven in-game bots. On the automotive side, NVIDIA has revealed new hardware and software platforms for autonomous driving, along with a giant list of partnerships. Companies from Toyota to Uber will build up their self-driving capabilities using NVIDIA's technology, which has now been certified by tough European regulators. NVIDIA is also partnering with Aurora and Continental to deploy driverless trucks at scale by 2027.

There was also a vision-enabled desktop assistant complete with a very impressive rendered avatar with voice mode. And that's all without mentioning the new range of consumer GPUs built on Blackwell architecture and a new data center chip with 72 Blackwell processors on the same wafer. The super chip was really something to see. Jensen kind of looked like Captain America carrying this thing across the stage like a shield. Now, in terms of response, the Neuron newsletter referred to this as NVIDIA's Apple moment, commenting, "'Remember when putting a personal computer on every desk and in every home changed the world?'

NVIDIA is more or less trying to do the same thing with AI supercomputers. Now to me what seems clear, and this has been coming for a while, is that NVIDIA is clearly running the playbook similar to Google from the early 2010s, where they shift focus from their one thing to try to capture as many related verticals as possible.

If NVIDIA can deliver on this bulky roadmap, it will have a competitive platform available for basically every use case of AI development, from language agents to industrial robots. They're also leaning heavily into open source, which will likely drive a massive price war among AI labs. All of this, of course, drives NVIDIA's core business of selling AI chips. The TLDR on their strategy? Make deploying AI in every aspect of life as friction-free as possible to drive demand for AI chips through the roof.

Now, funny enough, the implications kind of seemed lost on Wall Street. Bloomberg reported the event under the headline, NVIDIA's slides after unveiling leaves investors wanting more. I actually think that this is a total misunderstanding of what happened. NVIDIA's stock was down 6% yesterday, but I think that has much more to do with unrelated macroeconomic shocks than it does to do with investors not liking what Jensen had to say in Vegas. Indeed, stock analysts were at least a little less myopic, with

with Goldman Sachs writing that the quote, string of announcements at a minimum highlight the company's ability to innovate at industry-leading speed across hardware and software, as well as its robust partner and customer ecosystem. Ultimately, what this was, was an unveiling. NVIDIA has been inching away from being just a chip company to being an AI-first tech giant, and that couldn't have been clearer in this presentation. We'll wrap there. However, that's going to do it for today's AI Daily Brief. Appreciate you listening or watching as always. And until next time, peace.