The lightning speed emergence and evolution of OpenAI’s GPT platform, and of large language models (LLMs) in general, requires a reassessment of the innovation landscape and the economy itself. Exciting developments by giant tech companies and tinkering novices land not month by month but minute by minute. 

Each new era of digital advance marries a new abundance of hardware resources with an explosion of software creativity. Today, the Transformer approach to A.I., introduced in 2017, leverages the new silicon abundance – massive parallelism, embodied in graphics processors, or GPUs, themselves arrayed in massively parallel fashion in data centers. The result is a new knowledge platform, soon to unleash multidimensional cascades of software, content, and digital capability which will diffuse into every tool and industry. 

In 2016, DeepMind’s AlphaGo blew our minds by winning, with panache, an ancient board game far more complicated than chess. AlphaGo signaled a new era in A.I. We noted at the time, however, that it was still playing on a field constrained in multiple dimensions. It also consumed 50,000 times more powerthan the human brain. An impressive feat, yes, but voracious and narrow. 

ChatGPT’s emergence this winter, however, captured the world’s attention because of its seeming ability to deal with a wider range of tasks across a much broader, more ambiguous, more human field of play. Continue reading . . .

Writing is hard and time consuming. Thanks to ChatGPT, it just became far easier and faster. Rudimentary chat bots have been writing simple articles, such as sports game summaries, for years. ChatGPT, from artificial intelligence supernova OpenAI, leaps far beyond through its vast search of billions of internet texts and its ability to generate passable prose based on prompts and questions. It can even simulate software code. But it’s a Large Language Model, or LLM, so it is still not great at math, or lots of other things. It makes funny mistakes.

So what. It’s powerful enough to begin transforming dozens of tasks and businesses. And it doesn’t need to be perfect or even human-like to be the source of unimaginable mischief, too. Read more . . .

See our latest in The Hill: The Microchip Renaissance Needs More Than Money 

“The United States is pouring money into microchips, but will this fix the supply chain problem? The newly-passed CHIPS Act provides more than $75 billion for advanced fabrication of microchips in the U.S. and is the centerpiece of a strategic effort to boost domestic high-tech manufacturing.

“Money alone, however, is not enough. If policymakers don’t correct an array of obstacles across the high-tech supply chain, the CHIPS effort and America’s broader high-tech manufacturing strategy could falter.

“Over the past four decades, most of the world’s advanced semiconductor manufacturing capacity gravitated to Taiwan and nearby Asian locales, while the U.S. share of leading-edge capacity fell to around 12 percent. Low-wage labor was a factor, but enormous government subsidies were more important. Now, China and India are pushing additional subsidies and further undercutting the U.S. on a host of industrial regulatory burdens…” continue reading at The Hill . . .