I was pretty excited to watch $INTC 's Architecture day yesterday - very cool upcoming parts. Intel is definitely coming back…. then I watched $TSLA 's AI day… OMG... How will others compete with them on any autonomy use case? 👇Thread
1 -Tesla has created the most advanced SW architecture for perception, with recurring neural nets refining in real time and selectively their environment, with spacial and temporal queuing - exactly like we humans do. @dileeplearning @karpathy - you guys should talk!
2 -The above requires monster infrastructure to gather relevant video streams and label them for training. Tesla has a million cars on the road and INTEGRATED semi-auto labeling with >1,000 labelers. This is a key success factor. The above is impossible without it:
3 - Labeling video is not trivial. Neural nets doing that vastly exceed the size of the actual perception one inferring in the car. very hard to train. How could you outsource that to a third party?
4 - Training speed of all this infrastructure is the key driver of the pace of innovation. Iterative process. Tesla designed in-house a training pod, orders of magnitude faster than anything else, with unique architecture, possible only within an integrated organization.
5 - : 25 * 362 TFLOPs dies fanned out on a wafer make one tile. This means each tile is 30x faster than an Nvidia A100 GPU, 15x faster than Intel’s Pontevecchio!
6 - Each tile has 36Tbps I/O, i.e. one to two orders of magnitude more than anything Intel or Nvidia does in a single package. As @ElonMusk put it: success for Dojo is the SW team turning off the GPU cluster!!
7 - And for scale-out: 6 tiles per rack, 2 racks per cabinet. This means 1 Peta-flop per Tile, 25 per cabinet, and a 1 Exaflop training system with 10 Tbps bandwidth across all nodes, (bi-dimensional mesh), holding in only 40 cabinets. This is INSANE.
8 - Last but not least: The only bottle neck is talents. Tesla need the best A.I. engineers to run this operation and deliver the best AI, and given the toys they have, they will keep attracting the best!
9 - conclusion: Tesla is years ahead of anyone else for real-world perception A.I. and autonomy, has a fully integrated operation with the highest pace of innovation. Rings a bell? $Tesla is in A.I. EXACTLY where Tesla was in cars in 2011….
10 - The next ten years will be fun to watch!

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More from @p_ferragu

14 Sep
Some have asked me to be more specific. Quick thread, below. Not my area of expertise, so probably a lot of nonsense & ignorance, but my views at this point in time. In increasing order of importance and specificity; go to the bottom. for the full picture.
1) Taxing corporate is taxing everybody, competitive dynamics analysis shows tax hike gets into end-product price. Those spending more of their total income, i.e. not the richest ar hurt the most. This is govt taking more money not at all redistributing it towards the poorest.
2) Not taxing the super-rich friends making tax-shielded money, but only the upper middle folks, making real good money (>$400k), out of a real job or a real business they own. It is a) ethically wrong, demagogic, and divisive; b) counter-productive: fosters tax-shield strategies
Read 5 tweets
26 Aug
I have tried to figure out why $TSLA designed Dojo instead of using #Cerebras last night. I almost lost sleep on it and I don't have an answer yet. Any input welcome. Thread delow for where I stand.👇
1 - a fan out wafer of Dojo and a wafer-scale chip of Cerebras have similar transistor density (~2.5 Trillions). Dojo claims 9 PFLOPS BF16, Cerebras 2.5 PFLOPS half precision, which is about equivalent, I think. (3+X ratio between the two is fair-same as FP32/64 ratio on Ampere)
2 - Dojo plans to scale out to ~120 Wafers to get to Exascale. Cerebras announced yesterday at Hotchips 192. Both configurations are similar, and deliver exascale compute. Both architecture should be able to go beyond that if needed as well.
Read 7 tweets
21 May
The long awaited cash return on operating asset tweetstorm: $TSLA and $TSLAQ, anyone interested in investing and evaluating the FUNDAMENTAL RIGHT TO MAKE MONEY™ of a business should read this - our research on Tesla’s profitability is in the thread as well👇👇👇👇👇0 / 11
1 - What makes a right to make money™ ? Your ability to 1) invest some money into an operating asset 2) burn some cash to operate the asset and 3) generate cash from selling the resulting product or service, in excess of cash spent on running operations.
2 - A right to make money™ is more than a competitive advantage. It is a competitive advantage at producing something, which meets a need. which is valued at more than your cost of producing it. This is profound - as @ElonMusk would say.
Read 14 tweets
28 Jan
New narrative in the auto industry is that they have a software problem. Same as Nokia ten years ago. “We just need to invest in software to get back in the game”. Unfortunately this strategy failed; Nokia disappeared (in smartphones). Why? Thread below. $TSLA $BMWYY $DMLRY etc
First, investing in software doesn’t make sense. Software is a living animal, which starts like a baby, 3 guys in a dorm, and grows a full childhood before being grown up. If you “invest in software”, you create a Frankenstein. Ugly and dangerous.
Second, SW is the tip of the iceberg. The real key to success is end to end integration. Making a car like an iPhone. Perfectly pulled together. SW is where lack of integration is the most visible (can’t do OTA updates, our SW is fragmented), but integration matters everywhere.
Read 6 tweets

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