nomendos

Burden of proof is on LG, not on us and instead of they play dishonest games!

So, it is double-confirmed dishonesty and they should not be trusted further on EVER!

Factor in inflation (which is unusually high and looks to be continuing until productivity effects materialize), so there could be market pricing adjustments/corrections (maybe short crash too, with repricing), although it is an interesting race dynamic where AI is progressing >2x than any previous cycle. In any case AI profits will materialize as they are already materializing at fastest pace than any tech cycle. There could be other re-pricing moments such as amortization/ROI of the AI datacenter cloud-s**. Near-mid term we'll overbuild power and memory production capacity, both harvestable in continuation and will drop price of KWh and GB, while cloud/datacenter buildings will not have such continuation.

So, it is actually easy to see >$30T TAM by ~2030 - buckle up, as that would shake many things and who survives might get to either paradise or hell.

I'd welcome rational and logic substantiated thoughts on "Prediction: Nvidia Stock Price Will Skyrocket to This Range in 5 Years" (into range btw $1300 and $4K)

I was aware of market growth projections and I think there are many factors/bumps on that road. Additionally, investment in AI datacenters is already all or nothing kind of zero sum race, so much so that it has hit limits (power, available money, etc) so that there will be harder limits on such path (i.e. think of NVDA market cap value in a case of such valuations btw $35 and $75T which should fail this analysis). So, what do you think is more realistic (with sound end2end logic)?

Agree, such or similar unrealistic interviews are loss for both sides, plus they are plain STUPID. I've performed ~400 interviews that most included coding in my career with consistency and standardized report (can compare apple to apple).

At the very early phase of the boom I was among a very few who knew and predicted this (usually most free and deep thinking/knowledgeable). Then my prediction got reinforced by the results. One of the best examples was with one of my experiments that all today's AI's failed to solve tree serialization and de-serialization in each of the DFS(pre-order/in-order/post-order) or BFS(level-order) which is 8 algorithms (2x4) and the result was only 3 correct! Reason is "limited training inputs" since internet and open source does not have other solutions :-) .

So, I spent "some" time and implemented all 8, which took me few days. By the way this proves/demonstrates that ~15-30min pointless leetcode-like interviews are requiring to regurgitate/memorize/not-think. So, as a logical hard consequence there will.has-to be a "crash/cleanup" in the area of leetcode-like interviews as they will just be suddenly proclaimed as "pointless/stupid"). However, I decided not to publish the rest of the 5 solutions :-)

This (and other experiments) confirms hard limits of the LLM approach (even when used with chain-of-thought). Increasing the compute on the problem will produce increasingly smaller and smaller results (inverse exponential/logarithmic/diminishing-returns) = new AGI approach/design is needed and to my knowledge majority of the inve$tment (~99%) is in LLM, so "buckle up" at-some-point/soon?

Impacts and realities; LLM shall "run it's course" (produce some products/results/$$$, get reviewed/$corrected) and whoever survives after that pruning shall earn money on those products while investing in the new research to find new AGI design/approach (which could take quite a long time,... or not). NVDA is at the center of thi$ and time-wise this peak/turn/crash/correction is hard to predict (although I see it on the horizon and min/max time can be estimated). Be aware and alert. I'll stop here and hold my other number of thoughts/opinions/ideas for much deeper discussion. (BTW I am still "full in on NVDA" until,....)