David Luan: Why Nvidia Will Enter the Model Space & Models Will Enter the Chip Space | E1169

[@20VC]

Subscribe to the 20VC KZbin channel for more great interviews: www.youtube.com/@20VC

[@lailabouchrek3800]

د د

[@markoneil5279]

David’s honest, well informed input is much appreciated.

[@davab]

Agreed. Well spoken too this was a great insight for someone who is outside looking in

[@GardenOfSound594]

This has been the most insightful look into the future I've seen in recent times since Carl Shulman's interview by Dwarkesh Patel

[@enlaichu]

One of the best interviews I’ve seen in a long time. Both of you covered such broad and novel questions. David had such lucid, well-explained answers to Harry’s questions. Harry I love how good your questions were. All questions the audience would want to know the answers to. And your ability to peel the onion and keep diving down before changing the topic is phenomenal. You have a new subscriber!

[@ericgrinwis1630]

Exciting times for semiconductor stocks TSMC, AMD and NVDA. which are all experiencing a surge in value. It's interesting to watch the competition develop, given these stocks are major contributors to Al chip growth. On the increase of my personal holdings, I've witnessed amazing impact on my shares.

[@andyosman8375]

Intel and AMD will definitely have their share of the market. TSMC is at max capacity and investing in other semiconductor companies will be an absolute power move, Different chips are good at different things and Nvidia has been very specialised, which leaves other aspects of Al open.

[@davegustavo4726]

This is the type of in-depth detail on the semiconductor market that investors need, also the right moment to focus on the rewarding AI manifesto.

[@kaylagarrison9267]

Im unconvinced about intel future. Do you really think nvidia can keep up this surge rate and stream for the better part of the decade?

[@ericgrinwis1630]

certainly kayla, i had bought NVDA shares at $300, $475 cheap b4 the 10 for 1 split and with huge interest I keep adding, i’m currently doings the same for PLTR, POET and AMD constructively. Best possible way to get ahead, is participating behind top experienced performers.

[@AsandeMonwabisizondi]

i own three business, right now I'm compiling and picking stocks that l'd love to hold on to for a few years before retirement, do you think these stocks would do better over the years? My goal is to have at least $2 million saved for retirement.

[@adambohak1676]

This was a video that I needed to see. The content is getting better and better, Harry!

[@rajmankad2949]

This guy knows so much about so many things! Brilliant.

[@rishanchopra4719]

Another gem from 20VC!

[@sucim]

Very clear thinker! Amazing episode!

[@The_Uncertainity_Principal]

Ur a wizard harry !

[@firstnamesurname6550]

Excelent interview!! The fast way to implement 99.999(1) % safety self-driving vehicles in a city begins: 1) setting a sector where Human drivers are not allowed to drive in 2) Set that sector with cameras, move detectors and space scanners, all of that for modeling in real time the sector, let's call that 'A' dynamical set 3) Make the self driving vehicles to receive data from A. 4) by the exchange of data between A and each vehicle, the system will deploy patterns of predictability of vehicles, traffic, and anticipation ... plus, each vehicle and the system 'knowing' where/when one of each one is going on and each destiny. (for each vehicle) just by a subset of A, its own data, and a subset of date of the vehicles that surrounds it is enough ... like birds in a flock ... OK, pretty complicated (lot of subtasks don't exposed in the resume) and controversial(1) for westerners by denying human drivers in the sector ... but after observing the outcomes , see how traffic diminish , how people move faster and easier in the sector , how the vehicles move faster without crashing , and how the sector overall economy increase ... People would support to build new 'self-driving vehicles sectors' (1) the risks would come from animals or humans throwing things or themselves to the streets with bad intentions and/or suicidal attempts (but that can be anticipated by extending A sector to spaces from A where the vehicles doesn't circulate. During Earthquakes, it seems recommended to bypass activity, open the vehicle's doors and allow passengers to escape. (2) for preventing lags in the processes of development and implementation ... don't allow self driving vehicles out of the sector ... (**) China! Are you ready ?? Not new tech deployments required , just implementation of what already you have.

[@Perspectivemapper]

Such great insight from David for the near-term (1-5 year) business landscape.

[@MrGurosa]

Brilliant. If there was a button for "KZbin - show me this first, always", Id tap it.

[@darth.mingdom]

This video has a very high ratio of insights per min!

[@Lolleka]

He spent entire minutes just repeating obvious stuff.

[@GlobalMan-nr3hq]

David is right about Nvidia and this thought about getting into AGI type LLM must have come across Jensen Huang's mind. He is probably wary of pissing off his main customers currently and thus hurting NVidia's momentum. He is already doing NIMs which are LLMs in themselves but specialized ones but he isnt doing a major AGI LLM to go against OpenAI, Gemini etc - yet. I think he is just biding his time. He has a few avenues - acquisition of a startup or organically grown from within Nvidia. The former opportunities are dwindling - eg companies are already "coupled" with which AI startup. MSFT has their mitts on OpenAI, Amazon with Anthropic. Organically grown takes time to develop and its already late. Jensen knows that too. It'll be interesting to see his next moves.

[@mikezooper]

Apple will get their AI to learn live as users try to use it. It will fail but learn. Harry you are a brilliant interviewer. Also David was a great guest. Dual effort. Thank you.

[@dancingbird7225]

Wow, David is a genius, subscribed!

[@danielaraya1122]

Amazing interview, great questions

[@mikezooper]

An evolutionary learning algorithm that rewards efficient solutions, as it learns, is needed to save electricity and compute.

[@amonifinau4048]

Thank you!

[@bamh1re318]

Excellent interview! This the 2nd one I stayed through, besides of Jensen's

[@bamh1re318]

I have been using GPT, Perplexity and Nemotron4 almost daily for fun. Perplexity & Nemotron4 are in biology chats, never spit out BS

[@jessedbrown1980]

He got things wrong>>> Model performance in agents improves regardless of the Base level. You can see this in Agent Hospital. GPT4o can already be used to make 3 d printed objects just by using your voice. @David Luan He is a smart guy, but we can do better.

[@darknessguy4221]

This is so good!

[@thrivingthegrind6830]

It’s reasoning compute above base intelligence! Just like what Alex said!❤

[@leonlee877]

I still don't understand why we're in such a rush to create something that will make us irrelevant. How is that a good idea?

[@mosicr]

Acquihired by aws just 4 days after the release of the video.

[@mikezooper]

But we need the research phase to get transformers! The large problem solving teams only worked because of the research.

[@christopheraaron2412]

Perhaps we should thank God that that other s-curve is kind of like tapping out because there's got to be a certain point to where we just keep adding bigger hardware systems and then generate the power forum to where we'd literally have to start building them in space and then have a Dyson swarm take the sun's energy itself and beam it to a reactor to generate the power to run these things. We know that that's not economically viable. However just like what was being said just now about having the systems come up with a different paradigm to get smarter and smarter well then one of the best things about that is that instead of like doubling hardware which means you have to build it out and spend all this money these systems can just simply start becoming smarter and then perhaps even become smart enough in the not too distant future to engineer better versions of themselves that use less compute less energy maybe a little faster and also can perhaps engineer the next better version of themselves that once again uses less power for the same results.

[@williamx0]

With regards to T1 cloud providers needing to make models for the life of them to survive in the future... what is up with AWS... bedrock...? I guess they invested in Anthropic but... is that their business saving move? I would think they'd want to be more like Elon Musk and have their own brand of model like with xAI that's competing with the best.

[@johnny1tap]

I wrote a whole post about how deepmind solves unsolved problems only to go back and realize i misheard what you said in the intro.

[@Lolleka]

What did you get wrong?

[@BadWithNames123]

damn.. this guy is smart

[@christopheraaron2412]

Can't we generate lettuce synthetic data like especially it could harvest Dr Steven wolfram's digital physics programs and generate models and test them and then retrieve information from that especially seeing that for what I saw Dr wolfram's is using digital physics to run simulations that seem to mirror what we already observe in The real world. Wouldn't that basically translate into nearly infinite data?

[@throwaway6380]

He says "like" way too much