ChatGPT: How Sam Altman built the world’s hottest technology with billions from Microsoft – Fortune

In my view this will be the next monumental change in all industries, including the medical industry.

“This article appears in the February/March 2023 issue of Fortune with the headline, ChatGPT creates an A.I. frenzy.”

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Who here has used chatGPT for life and health extension and what were your results?

It’s very useful as a ‘personal learning assistant’, at least if it’s right. Like for example, you might be reading a study or an article and then prompt ChatGPT at the same time about things you don’t understand or ask questions about. You can learn about many different topics. Of course sometimes many times it’s wrong, but you can double check.

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Although it is fun to play with, ChatGPT is wrong quite a bit. I have fed it numerous clinical cases, and the doses prescribed were lethal in some cases. Currently, it can dispense simple advice on health strategies. On the other hand, it might just keep getting better over time.


I doubt it will get far better in the next decade and probably even in 2 decades it won’t be close to the point of a physician. I do enjoy the fairly believable radiology impressions though and perhaps those in non-interventional rads may want to be more wary.

It might seem that I’m biased and I’m certainly not an expert, but I’ll just point out I have some background knowledge and experience on ML and enough medical context to be fairly confident that my opinion would apply.


[quote=“tongMD, post:5, topic:5296”]
“I doubt it will get far better in the next decade and probably even in 2 decades”…
[/quote]…in your view

As was said about word processing programs, search engines{ do you remember AltaVista], a “cell phone” and many other items.

It is occuring right before your eye’s.

And no one will be able to stop it from occuring.


Program that do imaging{radiology] is a by product of the the defense industry.

What the “public” sees is a very small part of what is actually occuring.


You realize how long the field of AI has existed? 1950s. Several waves of the same exact exuberance you purport.

IBM Watson Health is pretty close to vaporware - I’ve said it for several years before it finally came to light - talked to people actually in it. I don’t base my opinion on “what the public sees”. Not only that, you’re missing the key fundamental inputs needed for training. Garbage in, garbage out.

I’m not bearish overall on technology btw, but you’re missing the point on how healthcare works operationally with siloing of data and regulatory risks at the very least. It seems you’re not aware of how medicine works either.

If I’m wrong, it’s likely most physician specialties will be one of the last jobs out - pretty close to a theoretical singularity where the plausibility is still debatable in the first place. At that point, it won’t matter, but it’s unlikely in the near term, any way you swing it - it’s pretty clear cut on both sides. The funny thing is Moore’s Law is part of the basis of theory, but Moore himself finds it implausible. I’m open to the plausibility but haven’t found convincing conclusive evidence either way.

See the Appendix University of Oxford on job automation probability and then review methods:

Would be interesting to train it only on peer reviewed research…


Its probably coming…

And a contrarian viewpoint

The Markup: Decoding the Hype About AI – The Markup.

I do like Arvind Narayanan. He talks a lot of sense.
His forthcoming book that’s referenced in your link (about “AI Snake oil”) should be well worth a read. He’s absolutely right that Chat GPT is about generating plausible, “Turing test beating” text rather than any attempt to discover or articulate the truth as a primary objective.

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All types of generative AI are getting better at explosive rates . . . you guys who think that certain scenarios are “years away” will be surprised at how different the world will be in just a few months.

In the few short weeks since I wrote the article below, a new text-to-speech generator was released that let me have AI narrate this entire video for me. I made this last night on my cell phone, while sitting on the couch with my kids:


“Lead, Follow or Get Out of the Way!”

This quote, alternately attributed to Thomas Paine and George Patton.

No one will be capable to stop what is occuring before your eyes in real time.

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Very impressive! Not much need for authors to do their own voice-readings for audio books any more - and this would be great for multi-language applications.


I am happy for solving protein folding for a step towards more rational drug design and additionally, eventually applying computer vision on organoids to shift to a factory-style high throughput screening for new pharmaceuticals - that’s rapid genuine progress if folks understood what actually was possible with a CS, computational bio/biochem, and ML/“AI” background.

I’m also incredibly happy there is a lot less of an “AI winter” relatively speaking for radiology as Medicare Technology payments are back in full swing. I have no qualms about what could potentially be possible in healthcare “AI”.

The problem is many people really do fall for what is termed “AI snake oil” in your link far too often, as you probably already know is fairly rampant in SV to raise funds “Theranos style” with only an Excel sheet in the back doing linear regression. At least the potential for human harm is less so with non-healthcare related AI.

The key part of the Theranos scam was there wasn’t any investors who were familiar with biotech and it was literally impossible for some of the things Holmes claimed…seen it way too often in a similar fashion for “AI” - people with no knowledge or context making far too optimistic predictions.

When you tell people off for Theranos and Watson Health at the time and explain directly why some things are literally impossible and other parts incredibly implausible, you’ll get the same responses.


Very nice, Who choose the soundtrack? Eerily, apropos.

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Absolutely - very few VCs have the necessary expertise to really do good due diligence on these types of startups, and with FOMO (fear of missing out), they just forge ahead with investments and hope that the lead investor knows what they are doing.

AI in healthcare is going to be a very slow development and adoption process… I think.

The FDA will have a lot of issues with certifying things where you can’t identify the exactly inputs (and the rationale) for a given output. I’ve worked in regular Tech (with the typical 6 month to 9 month product development cycles) and also in digital health. Digital health (that involves anything clinical or FDA) is just unbelievably slow by traditional tech traditions; years instead of months for clinical trials, FDA reviews, etc… And thats probably appropriate given the risks and consequences, but its a very different mindset and timeline for people coming out of consumer or business tech industries.


I chose it! Reminded me of the BladeRunner soundtrack.


BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining

Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Among the two main branches of pre-trained language models in the general language domain, i.e., BERT (and its variants) and GPT (and its variants), the first one has been extensively studied in the biomedical domain, such as BioBERT and PubMedBERT. While they have achieved great success on a variety of discriminative downstream biomedical tasks, the lack of generation ability constrains their application scope. In this paper, we propose BioGPT, a domain-specific generative Transformer language model pre-trained on large scale biomedical literature. We evaluate BioGPT on six biomedical NLP tasks and demonstrate that our model outperforms previous models on most tasks. Especially, we get 44.98%, 38.42% and 40.76% F1 score on BC5CDR, KD-DTI and DDI end-to-end relation extraction tasks respectively, and 78.2% accuracy on PubMedQA, creating a new record. Our larger model BioGPT-Large achieves 81.0% on PubMedQA. Our case study on text generation further demonstrates the advantage of BioGPT on biomedical literature to generate fluent descriptions for biomedical terms. Code is available at this https URL.



My view

The race is on, who will become the “defacto” standard in the field?

Just as PDF files became the defacto standard for business text.

This is occuring in real time before your eyes.

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There are likely going to be many different vertical markets where this tech can be applied (consumer, medical (Radiology/cardiology/neurology, etc.), chemical, biological, etc.). And the quality is largely based on how large the dataset is (and the quality of the dataset is) that you use to train the AI system - so people with the most good data will likely be the winners).

We’ve talked about this market for years in the silicon valley… most of us always assumed that Google is the natural company to dominate many of these AI markets because they have by far the most data to train their AI systems on (billions of users searching on everything for 15+ years). But there is always the “innovators dilemma”, issue of making obsolete your own products, which causes issues in companies.

Medical records are largely Silo’d in different medical record systems with all sorts of protections, etc… Its complex. We’ll see where this goes. It will be interesting to see how it evolves.

But yes, like PDF and many tech markets, these will likely be “winner take all” type of markets. The key question I have is how much protection / independence will different vertical markets have from each other. If a company “wins” in the consumer market, does that mean they are likely to win in a business or science or medical vertical market? That gets harder to call and will depend on how different the markets and data is.