He said that the person that was helping them train the domain-specific expert level AI was about to retire. Exactly, because anyone who trains domain-specific AI is about to retire their human job, whether they are ready or not. Until these companies have an answer to how they are going to honor the loyalty of these employees with loyalty FROM THE COMPANY that helps them get realistic LONG TERM, sustained training to keep them paid and relevant, the U.S. will not only remain pessimistic about AI, but expect that pessimism to ROCKET upwards as this tech is (pun intended) employed, while humans are no longer, more and more.
Capturing knowledge is challenging. All AI agents should have a CV profile that includes qualifications, work history, experience, and feedback ratings from humans. Then we can interview and onboard the agents using evidence and reference letters.
I'm going to guess that the answer is actually within your own question. It obviously was the most important part of the presentation and too good to put online here lol.
The biggest risk the US has is that almost all the Semiconductor company have their design centres in Israel as well. Now, any electronics have a very high risk of getting compromised, including turning into a bomb as we saw in Lebanon.
Lack of AI people with domaine knowledge is a big problem. A lot of them know a lot about AI but nothing about banking, manufacturing, health care, or any part of the real world.
I hate to be negative but manufacturers have been "capturing" domain specific process data for about 50 years. It is often written down but it is always captured and taught to younger employees. In die casting plants we have 60 process inputs and it is quite complex. I am sure that a chip fab is quite a bit more complex. Capturing the data is not new at all. Tha challenge is to know how to use the data to solve pocess problems, test the results and improve the process. This requires skilled people. AI will not be doing this any time soon.
You are correct and it’s not negative. In particular, in the semiconductor industry, we have long had extensive documentation and processes to capture operational expertise. The exciting opportunity today is that it has become much easier to capture and to operationalize using AI. Because today’s AI can much more readily “speak/understand” natural language and other sources of knowledge from our physical world.
I agree with the first part you said, however LLM does have reason capability but “training” it to consistently generating the right answer is a challenge, at the moment. For domain specific topic, it’s even harder. the training data set is proprietary, low volume, and the LLM was largely trained on noisy data which causing the result to be inconsistent and unreliable. But this can be engineered and corrected over time. It’s no longer impossible.
I disagree! It's not about AI solving the problem. AI as a tool can enable skills development using data and processes in the context of manufacturing.
@@edwardjones856 You have zero reason to say AI won't be doing it soon. How complex is programming? Making entire videos in seconds with a prompt? Imitating voices near perfectly. The AI merely needs to be trained on the correct data sets, the exact same ones that the humans would be using, and given the correct supervision and guidance during training. The presenter just spelled it out in THIS VIDEO. I'm sorry sir, but your insurmountable obstacles are EASILY solved, even at current AI levels and when AGI arrives, AGI will do ALL of the solving: period.
Initially, AI is an enabler. If it emerges in an ethically corrupted milieu it will enable corruption. Alternatively, it could facilitate the emergence of a society that measures performance against commitment, personal agency, responsibility, and equitability, a “great equalizer” promoting objectively wise outcomes. This is an existentially significant choice. Read Amaranthine: How to Create a Regenerative Civilization Using Artificial Intelligence
US wars from the past 30 years have only benefited one nation and it hasn't been the US. Unlikely that the US will end any wars anytime soon since every party is captured except the green.
@@The_Quaalude lol, good luck. All of that tech is proprietary to Taiwan and Taiwan only. Taking that your disabled country has constant leaks of military blueprints to chinese there is doubt that States are able to do anything at all. Nobody is scared or even respects usa rn. And idiots that scream about isolationism just continue to prove that nobody should believe in this failed state
I just don’t see how the pace of new knowledge creation does not end once the humans are all laid off or retired. Endless permutation of old by AI is not creation of the new.
I wonder if in the 'expert mode' contexts of GenAI, when we'll stop calling the over-confident, incorrect (and even made-up) responses 'hallucinations' and finally begin to call them 'bullshit' as we would call out GenAI's human analogues. But wait, GenAI has 'PhD level nunchuk skills'. We're talking super-PhD-impossible-to-bullshit level mega brain (with weaponry! ) here. Nah, why question 'it' either - that's far above our mortal pay grades ...
He said that the person that was helping them train the domain-specific expert level AI was about to retire. Exactly, because anyone who trains domain-specific AI is about to retire their human job, whether they are ready or not.
Until these companies have an answer to how they are going to honor the loyalty of these employees with loyalty FROM THE COMPANY that helps them get realistic LONG TERM, sustained training to keep them paid and relevant, the U.S. will not only remain pessimistic about AI, but expect that pessimism to ROCKET upwards as this tech is (pun intended) employed, while humans are no longer, more and more.
Capturing knowledge is challenging. All AI agents should have a CV profile that includes qualifications, work history, experience, and feedback ratings from humans. Then we can interview and onboard the agents using evidence and reference letters.
This is exactly what's going to happen.
I really enjoyed this, especially at the end when the SOP question came up!
Why did you edit out the most important part of the presentation?
What was the most important past that was edited out?
Please explain.
I'm going to guess that the answer is actually within your own question. It obviously was the most important part of the presentation and too good to put online here lol.
16:54 that’s the part being edited and cut
@@tracytsaiwhat was Nguyen talking about in that cutted part? Could you please tell us :)
Ai agents will do many things for us in the future.
I found this a useful talk. for a non tech person looking for high level understanding. thanks.
Great to hear!
The biggest risk the US has is that almost all the Semiconductor company have their design centres in Israel as well. Now, any electronics have a very high risk of getting compromised, including turning into a bomb as we saw in Lebanon.
Would there be any jobs for entry level fresh grads in this domain and how to get those jobs and what companies are hiring?
Does anyone have acess to the presentation?
Lack of AI people with domaine knowledge is a big problem. A lot of them know a lot about AI but nothing about banking, manufacturing, health care, or any part of the real world.
I hate to be negative but manufacturers have been "capturing" domain specific process data for about 50 years. It is often written down but it is always captured and taught to younger employees. In die casting plants we have 60 process inputs and it is quite complex. I am sure that a chip fab is quite a bit more complex. Capturing the data is not new at all. Tha challenge is to know how to use the data to solve pocess problems, test the results and improve the process. This requires skilled people. AI will not be doing this any time soon.
You are correct and it’s not negative. In particular, in the semiconductor industry, we have long had extensive documentation and processes to capture operational expertise. The exciting opportunity today is that it has become much easier to capture and to operationalize using AI. Because today’s AI can much more readily “speak/understand” natural language and other sources of knowledge from our physical world.
I agree with the first part you said, however LLM does have reason capability but “training” it to consistently generating the right answer is a challenge, at the moment. For domain specific topic, it’s even harder. the training data set is proprietary, low volume, and the LLM was largely trained on noisy data which causing the result to be inconsistent and unreliable. But this can be engineered and corrected over time. It’s no longer impossible.
I disagree! It's not about AI solving the problem. AI as a tool can enable skills development using data and processes in the context of manufacturing.
@@edwardjones856 You have zero reason to say AI won't be doing it soon. How complex is programming? Making entire videos in seconds with a prompt? Imitating voices near perfectly. The AI merely needs to be trained on the correct data sets, the exact same ones that the humans would be using, and given the correct supervision and guidance during training. The presenter just spelled it out in THIS VIDEO. I'm sorry sir, but your insurmountable obstacles are EASILY solved, even at current AI levels and when AGI arrives, AGI will do ALL of the solving: period.
Initially, AI is an enabler. If it emerges in an ethically corrupted milieu it will enable corruption. Alternatively, it could facilitate the emergence of a society that measures performance against commitment, personal agency, responsibility, and equitability, a “great equalizer” promoting objectively wise outcomes. This is an existentially significant choice. Read Amaranthine: How to Create a Regenerative Civilization Using Artificial Intelligence
and "the stuff which is not in those documents" is so much...
Exactly. And humans keep generating this stuff.
Esoteric ..
US must detach herself from all types of wars, focus on innovation and it's mass scale use to create competitive edge.
US wars from the past 30 years have only benefited one nation and it hasn't been the US. Unlikely that the US will end any wars anytime soon since every party is captured except the green.
remind me where would you buy microchips without Taiwan?
@@Dmytro-kt3frexactly why America needs to start manufacturing again
@@The_Quaalude lol, good luck. All of that tech is proprietary to Taiwan and Taiwan only. Taking that your disabled country has constant leaks of military blueprints to chinese there is doubt that States are able to do anything at all. Nobody is scared or even respects usa rn.
And idiots that scream about isolationism just continue to prove that nobody should believe in this failed state
Is this not why PLTR ontology is so important
I just don’t see how the pace of new knowledge creation does not end once the humans are all laid off or retired. Endless permutation of old by AI is not creation of the new.
only the domain expert in engineering are able to implement the AI . IT and CS people have limitation
the only ones who will benefit from AI are the rich
I wonder if in the 'expert mode' contexts of GenAI, when we'll stop calling the over-confident, incorrect (and even made-up) responses 'hallucinations' and finally begin to call them 'bullshit' as we would call out GenAI's human analogues. But wait, GenAI has 'PhD level nunchuk skills'. We're talking super-PhD-impossible-to-bullshit level mega brain (with weaponry! ) here. Nah, why question 'it' either - that's far above our mortal pay grades ...
yet he provides no evidence that they work better. just claims. how is this remotely scientific.
I think you confused about what this is.
Hi please come see me how we are using agents to build 200,000 word legal contracts
Send the link
US is No. 1 in innovation but China Master it's use it then build upgraded version.