Artificial Intelligence and You

The first area to see a dramatic impact from #ChatGPT was when it crushed term papers and sent teachers scurrying for ways to assess their students. Now that we've had nearly a year to evaluate the impact of #AI on #education, I look at how assessments and teaching have been affected and how schools might adapt to the incredible opportunities of generative AI.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

What effect will #AI, especially large language models like #ChatGPT, have on jobs? The conversation is intense and fractious. I attempt to shed some light on those effects, and discuss some of the different predictions and proposals for distributing the dividend from reducing costs and increasing markets through deploying AI. How will that capital get to where it is needed?

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

The United Kingdom government is holding a Summit on Artificial Intelligence at the storied Bletchley Park on November 1 and 2. Luminaries of #AI will be helping government authorities understand the issues that could require regulation or other government intervention.

Our invitation to attend may have been lost in the post.

But I do have reflections on the AI risks that will (or should) be presented at this event and some analysis and thought-provoking questions prompted by excellent events on these topics I recently attended by the London Futurists and MKAI.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

Radiology found itself in the crosshairs of the debate about AI automating jobs when in 2016 AI expert Geoffrey Hinton said that AI would do just that to radiologists. That hasn't happened - but will it?  To get to the bottom of this, I talked with Matthew Lungren, MD, Chief Medical Information Officer at Nuance Communications, a Microsoft company applying AI to healthcare workflows, and the name that comes at the top of the list when you look up #radiology and #AI. He also has a pediatric radiology practice at UCSF  and previously led the Stanford [University] Center for Artificial Intelligence in Medicine and Imaging. More recently he served as Principal for Clinical AI/ML at Amazon Web Services in World Wide Public Sector Healthcare. He has an impressive oeuvre of over 100 publications, including work on multi-modal data fusion models for healthcare applications, and new computer vision and natural language processing approaches for healthcare-specific domains.

In this interview conclusion, we talk about the details of how AI including large language models can be an effective part of a radiologist’s workflow how decisions about integrating AI into medicine can be made, and where we might be going with it in the future.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

Radiology found itself in the crosshairs of the debate about AI automating jobs when in 2016 AI expert Geoffrey Hinton said that AI would do just that to radiologists. That hasn't happened - but will it?  To get to the bottom of this, I talked with Matthew Lungren, MD, Chief Medical Information Officer at Nuance Communications, a Microsoft company applying AI to healthcare workflows, and the name that comes at the top of the list when you look up #radiology and #AI. He also has a pediatric radiology practice at UCSF  and previously led the Stanford [University] Center for Artificial Intelligence in Medicine and Imaging. More recently he served as Principal for Clinical AI/ML at Amazon Web Services in World Wide Public Sector Healthcare. He has an impressive oeuvre of over 100 publications, including work on multi-modal data fusion models for healthcare applications, and new computer vision and natural language processing approaches for healthcare-specific domains.

The basis for Hinton's assertion was that AI can be trained to find tumors, for instance, in CT scans, and we know how good AI is at image analysis when it’s got lots of labeled data to be trained on, and we certainly have that with CT scans.  We get to find out what's real about AI in #medicine in this episode.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

The superheated large language model (LLM) revolution is only accelerating as they are incorporated into #agents - systems that take independent action. Here to help us understand the state of that art is Michael Sharpe, CEO of Magick ML, a development environment that gives people a way of creating agents based upon generative #AI. Equally fascinating is Michael's previous job at Latitude, working on the virally popular on-line fantasy adventure game of Dungeon AI, a role-playing simulation where the story was made up by an #LLM on the fly, and we talk about that too.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

Robots - embedded AI - haven't gotten the adulation that large language models have received for their recent breakthroughs, but when they do, it will be thanks in large part to Hod Lipson, professor of Mechanical Engineering at Columbia University, where he directs the Creative Machines Lab, which pioneers new ways to make machines that create, and machines that are creative. He received both DARPA and NSF faculty awards as well as being named Esquire magazine’s “Best & Brightest”, and one of Forbes’ “Top 7 Data scientists in the world.” His TED talk on building robots that are self-aware is one of the most viewed on AI, and in January 2023 he was centrally featured by the New York Times in their piece “What’s ahead for AI.” He is co-author of the award-winning books “Fabricated: The New World of 3D printing” and “Driverless: Intelligent cars and the road ahead”. Hod is a deeply passionate communicator who is driven to help people understand what’s going on with #AI and #robotics.

In the conclusion of the interview we talk about robot cannibals, self-replicating robots, novel form factors for robots, the impact of #ChatGPT on higher education, and more of Hod's expansive vision for the future.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

Robots - embedded AI - haven't gotten the adulation that large language models have received for their recent breakthroughs, but when they do, it will be thanks in large part to Hod Lipson, professor of Mechanical Engineering at Columbia University, where he directs the Creative Machines Lab, which pioneers new ways to make machines that create, and machines that are creative. He received both DARPA and NSF faculty awards as well as being named Esquire magazine’s “Best & Brightest”, and one of Forbes’ “Top 7 Data scientists in the world.” His TED talk on building robots that are self-aware is one of the most viewed on AI, and in January 2023 he was centrally featured by the New York Times in their piece “What’s ahead for AI.” He is co-author of the award-winning books “Fabricated: The New World of 3D printing” and “Driverless: Intelligent cars and the road ahead”. Hod is a deeply passionate communicator who is driven to help people understand what’s going on with #AI and #robotics.

In part 1 we talk about our future with #robots that might be creative, self-aware, sentient, or generally intelligent.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.