Jeffrey Funk

Fellow, Walter Bradley Center for Natural and Artificial Intelligence

Archives

The Value and Drawbacks of ChatGPT

In this week’s episode, Robert Marks resumes his conversation with tech consultant and expert Jeffrey Funk. They focus on ChatGPT, its value and limits, and the hype that often accompanies new developments in AI. Additional Resources Robert J. Marks at Discovery.org Jeffery Funk at Discovery.org Artificial Intelligence: Will Machines Take Over (Science Uprising) Three Things AI Machines Won’t Be Able to Achieve Podcast

Where Does Innovation Come From? 

In a continuation of last week’s conversation, technology experts Jeffrey Funk and Robert J. Marks explore the question of where today’s technological innovation is fostered. Academia? Private corporations? The military? Since many universities now prize publication over innovation, much of the real progress is being made elsewhere.  Additional Resources Robert J. Marks at Discovery.org Jeffery Funk at Discovery.org Podcast

Jeffrey Funk on AI, Startups, and Big Tech

In this podcast episode, technology consultant and author Jeffrey Funk joins Robert J. Marks to talk about the artificial intelligence industry, how it’s used by Big Tech, and AI’s exaggerated hype.  How do we respond to AI when technology is changing every year? Additional Resources Robert J. Marks at Discovery.org Jeffery Funk at Discovery.org Podcast

Does New A.I. Live Up to the Hype?

Experts are finding ChatGPT and other LLMs unimpressive, but investors aren't getting the memo
Original article was featured at Salon on February 21st, 2023. On November 30, 2022, OpenAI announced the public release of ChatGPT-3, a large language model (LLM) that can engage in astonishingly human-like conversations and answer an incredible variety of questions. Three weeks later, Google’s management — wary that they had been publicly eclipsed by a competitor in the artificial intelligence technology space — issued a “Code Red” to staff. Google’s core business is its search engine, which currently accounts for 84% of the global search market. Their search engine is so dominant that searching the internet is generically called “googling.” When a user poses a search request, Google’s search engine returns dozens of helpful

Goodhart’s Law and Scientific Innovation in Academia

Many university researchers are leaving academia so they can actually get things done
British economist Charles Goodhart was a financial advisor to the Bank of England from 1968 to 1985, a period during which many economists (“monetarists”) believed that central banks should ignore unemployment and interest rates. Instead, they believed that central banks should focus on maintaining a steady rate of growth of the money supply. The core idea was that central banks could ignore economic booms and busts because they are short-lived and self-correcting (Ha! Ha!) and should, instead, keep some measure of the money supply growing at a constant rate in order to keep the rate of inflation low and constant. The choice of which money supply to target was based on how closely it was statistically correlated with GDP. The British monetary authorities adopted this policy in

Large Language Models Can Entertain but Are They Useful?

Humans who value correct responses will need to fact-check everything LLMs generate
In 1987 economics Nobel Laureate Robert Solow said that the computer age was everywhere—except in productivity data. A similar thing could be said about AI today: It dominates tech news but does not seem to have boosted productivity a whit. In fact, productivity growth has been declining since Solow’s observation. Productivity increased by an average of 2.7% a year from 1948 to 1986, by less than 2% a year from 1987 to 2022. Labor productivity is the amount of goods and services we produce in a given amount of time—output per hour. More productive workers can build more cars, construct more houses, and educate more children. More productive workers can also enjoy more free time. If workers can do in four days what use to take five days, they can produce 25 percent more—or

Tech bubble? Our Progress Towards Value to Users Has Slowed…

We should be wary of glowing forecasts when newer technologies don’t offer anywhere near as large benefits
Today’s new technologies, from virtual reality to nuclear fusion have recently received record investments from venture capitalists, but their revenues are not growing as fast as technologies of past decades. Startup losses are unprecedented — far larger than in past decades. Share prices and private valuations have also been collapsing in 2022. Optimists mostly focus on the good news and ignore these facts. They believe that the heavy funding for these new technologies is a good measure of potential and thus any criticism is unjustified. Here is their typical argument: Paul Krugman and other “experts” criticized the Internet, personal computers, and other technologies in their early years. But these technologies succeeded. Therefore, criticisms of the new technologies are

The Hyper-Specialization of University Researchers

So many papers are published today in increasingly narrow specialties that, if there is still a big picture, hardly anyone can see it
The Bible warns that, “Of making many books there is no end; and much study is a weariness of the flesh.” Nowadays, the endless making of books is dwarfed by the relentless firehose of academic research papers. A 2010 study published in the British Medical Journal reported that the U.S. National Library of Medicine includes 113,976 papers on echocardiography — which would weary the flesh of any newly credentialed doctor specializing in echocardiography: We assumed that he or she could read five papers an hour (one every 10 minutes, followed by a break of 10 minutes) for eight hours a day, five days a week, and 50 weeks a year; this gives a capacity of 10000 papers in one year. Reading all papers referring to echocardiography… would take 11 years and 124 days, by which time at

How Far Will Unicorn Share Prices Fall?

Cumulative losses give us some insights
Most investors know that America’s Unicorns are losing money. What they don’t know is that most Unicorns have dug big holes for themselves and aren’t sure how to dig themselves out. What do I mean by holes? I mean massive cumulative losses that have been accumulated over many years of yearly losses. Because many of today’s Unicorn startups were founded at least 10 years ago, and are still unprofitable, they have a had a long time to create huge cumulative losses, some much more than the $3 billion that Amazon once had. The biggest losses are for Uber ($29.1 billion), WeWork ($12.2 billion), Snap ($8.7 billion), Lyft ($8.5 billion), Teledoc Health ($8.1 billion), and Airbnb ($6.4 billion), followed by four others (Nutanix, Rivian, RobinHood and Bloom Energy) with greater than

Is Rationality Finally Emerging for Unicorn Share Prices?

Share prices are falling as losses continue to mount
2021 was a great year globally for venture capital and startups. Initial public offerings (IPOs) raised a record $594 billion in 2021 globally while VC funding is on track to hit a record $454 billion invested through the first three quarters of 2021.This is up from $332 billion for the first three quarters of 2020, which was the previous record for three quarters. U.S. startups also did well with big increases in both VC funding and IPOs in 2021. Almost $100 billion of funding was given to startups in the first three quarters while for the full year, there were 416 IPOs, of which 128 were from the tech section. The total amount raised was $156 billion, of which $69 billion was for the tech sector. On the other hand, share prices are falling driven by

Destructing the Creative Destruction Myth

Debunking the argument that the Fortune 100 list is evidence of the productive vitality of capitalism
Joseph Schumpeter argued that capitalist economies are not stagnant and calcified but, instead, by nature a form or method of economic change and not only never is but never can be stationary.Joseph A. Schumpeter, Capitalism, Socialism, and Democracy, 1950 He believed that embedded in capitalism is an engine of change that revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one. This process of Creative Destruction is the essential fact about capitalism. It is what capitalism consists in and what every capitalist concern has got to live in.Joseph A. Schumpeter, Capitalism, Socialism, and Democracy, 1950 Schumpeter was no doubt influenced by Charles Darwin’s theory of evolution.

A World Without Work? Don’t Hold Your Breath

Predictions of mass unemployment caused by robots continue to be wildly inaccurate
Will we soon be sitting on couches watching reality TV shows while robots work 24/7 doing all of the work humans used to do? The idea that robots will replace most human labor has been around for almost 100 years and has become more popular with each new advance, from sensors and microprocessors to enterprise software, data analytics, and AI. A World Without Work by Daniel Susskind The latest wave of robot hysteria was tweaked by The Singularity is Near in 2005, emboldened by Race Against the Machine in 2012, and sent over the top by The Second Machine Age and The Rise of Robots in 2016, and A World Without Work in 2020, all best sellers. A World Without Work was shortlisted for the Financial Times & McKinsey 2020 Business Book of the Year, in addition to being

AI’s Future: Combining RPA With AI to Augment Knowledge Workers

The work machines can’t do is usually the rewarding part, both personally and financially
Counterterrorism requires analysts to work through millions of Twitter and Facebook messages, YouTube videos, and websites in multiple languages, far too much work for humans. But a combination of AI (artificial intelligence) and RPA (robotic process automation) can help humans do this work, leaving humans in charge of the most complex and important decisions. AI systems can crawl through documents in any language, automatically translating them, extracting names of people and organizations, and doing sentiment analysis of conversations to identify key text to be considered later by humans. This text can be automatically organized into proper bins using RPA, enabling a data processing and analytics pipeline that can handle large amounts of content at speeds never possible in the

Why We Need to Stop Relying On Patents to Measure Innovation

The key to a nation's long-run economic growth is the effect of innovation on productivity, and has little to do with patent activity
Patent databases may be a smoke screen that hides the true issues, problems, and dynamics of innovation behind the illusion that innovation is booming—and that patent activity measures the boom.  We are said to live in a time of remarkable innovation, with the computer/information revolution often compared to the Industrial Revolution in allowing people to produce more while working less. Economists, consultants, and other business gurus are striving mightily to quantify this revolution and to understand its sources and implications. One popular metric is the number of new patents issued each year. For example, the pace of innovation might be gauged by the fact that there were 669,434 US patent applications and 390,499 new patents awarded in 2019, each triple the

Where Have All the Profitable Startups Gone?

We must distinguish between COVID-19's devastating impact and pre-existing problems that it is making worse

The most successful startups of today aren’t as profitable as those founded 20 to 50 years ago. Something is terribly wrong with the current startup system.

Stanford’s AI Index Report: How Much Is BS?

Some measurements of AI’s economic impact sound like the metrics that fueled the dot-com bubble

Stanford University’s AI index offers us fanciful measures of the triumph of AI, rivaling the far-fetched metrics of dot-com commerce. The reality has been the opposite. For decades, U.S. productivity grew by about 3% a year. Then, after 1970, it slowed to 1.5% a year, then 1%, now about 0.5%. Perhaps we are spending too much time on our smartphones.