The essential pillars of democracy are:
1) freedom of expression
2) habeas corpus
3) balance of powers
4) alternance
5) constitutional reference
If you vote democrats at the next election, you lose 4 out of 5. Be a real democrat, defend democracy: vote for the other camp.
👇 Democracy is not about the popular vote.

The tyranny of the majority is not democracy.

Anyone insisting on the popular vote is a tyrant in the making. "I have the Popular vote so I do whatever I want".

Think Putin. Elected every time.

Long overdue research thread on what a world, in which $400bn are spent on datacenter AI chip in 2027, would look like
👇 $NVDA $AMD $AVGO $ANET and many others. First, here is what $400bn spent on AI chips in 2027 would look like: GPU and TPU shipments quadrupling, Other in-house accelerators ramping to represent 2x the TPU footprint.

What to expect for $TSLA auto gross margin next week? Well... brace for a - short-term, disappointment, with a further slide in 2Q23... But also a good recovery beyond. Here is how we looked at it 👇 Tesla lowered prices materially since the end of last summer. A great move, as it kept the company on track to grow deliveries ~50% p.a. This comes at a cost, though, driving gross margins down, from a peak of 30%, to 18.3% last quarter, adjusted for credits and leasing.

A bear arguments on $NVDA is that hyperscalers will deploy their own chips to replace GPUs. The argument has been around for a while and doesn’t seem to materialize, beyond $GOOG and the TPU. Why? The promised thread. 1/9 👇 It is true that the TPU costs 3-4x less than a GPU, first because it is a less beefed-up chip (smaller die, less HBM), and also because Broadcom, who manufactures the TPU for Google, takes a lower margin. 2/9

I find the $TSLA controversy price cut vs. advertising spending interesting. My (strong) view: any dollar spent on advertising by Tesla today would be a waste for everybody: the company, investors, and clients. 👇 Spending on advertising is about 1) growing brand awareness (people know about your products) 2) growing perceived quality, differentiation, and relevance.

I haven’t seen a single right take on Tesla’s announcement about silicon carbide yesterday (excepting ours, of course.) let me explain: The Silicon Carbide content of a Model 3 is ~$500. The main inverter is pure SiC. In the « Model2 », that cost is not acceptable.

My 5 takes on $TSLA CMD:

#1 Electrified civilization is coming. It is now unstoppable.
It is a very obvious fact and I am surprised it is widely overlooked. #2 20m cars and 1TWh « as soon as possible » is $1tn in revenues, >$200bn in profits and >$5tn in market cap. IMO doable in 2030 or shortly after. There is no Robotaxi, no Optimus, no Insurance, no perception AI platform in this.

Model 2 is critical to the continued success of $TSLA, and we should learn a lot more this week about it. Here is an overview of what we expect in 4 slides.👇 We expect Model 2 15% shorter, 30% lighter and 25% smaller battery than Model 3. We looked at how ICE compacts compare to mid-size ICE sedans and extrapolated the comparison between Model 3 and ICE mid-size sedans to reach this conclusion.

Quick thoughts on what dragged down the $TSLA stock this year, and what to expect next, in 10 tweets. 👇 1) Must be put into context. 2/3 of it is the broader correction of long-duration growth names.

After enjoying $TSLA #TESLA #FSDBeta, at last. My 2 impressions:👇 #1 - Awesome! Quality of the experience is exceptional. I was stunned and I was expecting much less. My car drove me to Mass today, and back, Alleluia! 😂. The quality of perception, handling complex and uncertain situations... Waow. Best A.I.-based product I know in the world.

A short thread on accelerated computing. How $TSLA's #Dojo, $GOOG's #TPU #Cerebras's #WSE-2, #Graphcore's #IPU, and others compare to $NVDA 's #GPU. This is an extract of work we published a few weeks ago. 👇1/6 It is difficult to compare chips. Designing a chip is all about managing trade-offs between multiple dimensions. A chip has limited potential resources and the architect allocates them over these multiple dimensions. 2/6

Quick thread of $TSLA Dojo vs. $FB Meta’s RSC 👇👇👇Fun side note, as I write a note comparing architectures: Microsoft doesn’t even recognize the word exascale in its dictionary. They are running behind big time! 😂 More seriously: in a single tweet - RSC will be 5x larger than Dojo in terms of computing power, but an order of magnitude behind on through-bandwidth per transistor. Details 👇👇

Hertz Buying 100k Tesla, my quick take: 👇 1) @ $42k per car, probably no discount, and it makes sense, why would Tesla sell at a discount while they won't be able to meet fully demand for years?

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.

https://twitter.com/p_ferragu/status/1437619096338714630

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.

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)

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!

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.

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.