AMD announced the Ryzen 8040 series of laptop processors at the company's AI-themed event, reframing what has been a conversation about CPU speed, power, and battery life into one that prioritizes AI. In January, AMD launched the Ryzen 7000 family, of which the Ryzen 7040 included the first use of what AMD then called its XDNA architecture, powering Ryzen AI. (When rival Intel disclosed its Meteor Lake processor this past summer, Intel began referring to the AI accelerator as an NPU, and the name stuck.) More than 50 laptop models already ship with Ryzen AI, executives said. In AMD's case, the XDNA NPU assists the Zen CPU, with the Radeon RDNA architecture of the GPU powering graphics. But all three logic components work harmoniously, contributing to the greater whole.

Investors, perhaps searching for a foundation upon which to lay their AI investments, appear to have found one: Nvidia, whose market capitalization Tuesday makes it the first trillion-dollar chip maker. At press time, Nvidia's stock price had jumped to $409.76 per share, giving it a market capitalization of $1.014 trillion. Nvidia's fortunes soared last week, when the company reported net income of $2.04 billion on revenue of $7.192 billion. Surprisingly, revenues fell 13 percent from a year ago. Investors ignored that, however, as Nvidia estimated that the current quarter would bring in $11.0 billion in revenue, an almost unheard-of quarter-over-quarter increase.

Always has been, always wi– Wait, what? Every company seeks to expand beyond its core market, both to satisfy shareholders as well as grow its sales opportunities. Intel has spent a lot of time and money over the years trying to move beyond processors alone and test the waters as a consumer brand. You could see the evolution: the Intel chime (dumdumdumDUM!), the dancing bunny people, the expansion into various parts of the PC… and beyond. Intel's core business, though, has always had an underlying goal: sell more chips.

Intel is expected to report a sharp drop in quarterly earnings, hurt by a rapidly shrinking market for personal computers that its chips go into. The company after the closing bell Thursday is projected to post sales of about $15 billion during the quarter ended in September, a retreat of more than 21% from the year-earlier period, according to a FactSet survey of analysts. Net income likely fell by around 93% to $494 million, the analysts estimate. Intel and other chip makers cashed in on a boom in computer and electronics sales at the outset of the pandemic with the shift toward remote work and distance learning. The market has turned, though, with high inflation, rising interest rates and recession fears that have weighed on demand.

President Joe Biden on Tuesday will sign a bill to provide $52.7 billion in subsidies for U.S. semiconductor production and research and to boost efforts to make the United States more competitive with China's science and technology efforts. The White House is touting investments that chip companies are making even though it remains unclear when the U.S. Commerce Department will write rules for reviewing grant awards and how long it will take to underwrite projects. The chief executives of Micron, Intel, Lockheed Martin, HP and Advanced Micro Devices will attend the signing, set for 10 a.m. EDT, as will cabinet officials and auto industry and union leaders, including United Auto Workers President Ray Curry, the White House said. Also attending will be governors of Pennsylvania and Illinois, the mayors of Detroit, Cleveland and Salt Lake City, and lawmakers. The White House said the bill's passage was spurring new chip investments.

The raw computational power necessary to use machine learning has dwarfed everything else we use computer chips to accomplish by an order of magnitude. And that appetite for power has created a booming market for chip startups for the first time in years and helped double venture capital investments over the past five years. AI market leader Nvidia estimates that most machine-learning or AI tasks have spurred a 25-fold increase in the need for processing power every two years, while one of the most advanced natural-language-processing models needs 275 times the compute power every two years to work. The boom has also created opportunities for a new breed of chip company, one that is focused on making specialized chips for AI. Prior to 2015 only a small handful of venture capitalists saw the opportunity that AI presented, and there was little overall interest in funding chip companies.

Over the past 12 months, the Philadelphia Semiconductor Index rallied about 90% as global demand for chips surged through the pandemic. Stay-at-home trends boosted sales of new PCs, data centers installed more chips to keep pace with the surging usage of cloud and AI services, and new technologies -- including driverless cars, automated factories, and 5G networks and devices -- gobbled up more chips. That demand propelled the price of many leading chip stocks, including Qualcomm, Advanced Micro Devices (NASDAQ:AMD), and NVIDIA (NASDAQ:NVDA), to historic highs. Taiwan's Taiwan Semiconductor Manufacturing (NYSE:TSM), the world's largest contract chipmaker, also benefited from those surging orders. The global semiconductor market could still expand at a compound annual growth rate of 10% from 2021 to 2026, according to research firm EMR, as companies across a wide range of industries purchase more chips.

When we consider earlier technology waves, there is often one company (or possibly two) that emerges as a leader and becomes synonymous with the technology. Mainframes became synonymous with IBM, virtualization spawned VMware, open source gave us Red Hat, web search was reinvigorated by Google, and social networks gave us Facebook and Twitter. We would argue that this has yet to happen with AI and machine learning (ML). AI – and its variants, notably machine learning – is an enabling technology. It enables computers to do things that weren't possible in earlier programming paradigms. With modern cloud computing, networking and storage, those things can be done at a scale unimaginable when the term'artificial intelligence' was first coined in the mid-1950s.

Nvidia CEO Jensen Huang likes to joke around. He once said Nvidia was 30 days from going out of business just to inspire his engineers. Many years ago, that was true. But considering Nvidia is now the most valuable chip company in the U.S., with a market capitalization of $310.8 billion, I think he has lost all credibility on that remark. But Huang likes to remember Nvidia's humble roots as it becomes a behemoth in AI and graphics chips.

One of the effects of the ongoing trade war between the US and China is likely to be the accelerated development of what are being called "artificial intelligence chips", or AI chips for short, also sometimes referred to as AI accelerators. AI chips could play a critical role in economic growth going forward because they will inevitably feature in cars, which are becoming increasingly autonomous; smart homes, where electronic devices are becoming more intelligent; robotics, obviously; and many other technologies. AI chips, as the term suggests, refers to a new generation of microprocessors which are specifically designed to process artificial intelligence tasks faster, using less power. Obvious, you might think, but some might wonder what the difference between an AI chip and a regular chip would be when all chips of any type process zeros and ones – a typical processor, after all, is actually capable of AI tasks. Graphics-processing units are particularly good at AI-like tasks, which is why they form the basis for many of the AI chips being developed and offered today. Without getting out of our depth, while a general microprocessor is an all-purpose system, AI processors are embedded with logic gates and highly parallel calculation systems that are more suited to typical AI tasks such as image processing, machine vision, machine learning, deep learning, artificial neural networks, and so on. Maybe one could use cars as metaphors. A general microprocessor is your typical family car that might have good speed and steering capabilities.