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🤖 Moore's law never ended - it moved to GPUs and expert systems go next level

Chamath's framing (credited to Adam D'Angelo): Moore's law did not end, it shifted to GPUs, because parallelization solves what CPU scaling could not. That moves the surface area of compute innovation to machine-learned models you can now brute-force - DALL-E and GPT-3 are the visible output - so 'all kinds of expert systems' become dramatically more capable, compounded by the training corpora and cloud capacity now available. The economics accrue to the accelerated-compute supply chain.

0 CONVICTION
peaked 75.6 GREEN
WATCH
band · contested
▲ LONG NVDA
expression · bullish tech
HIT
outcome · R +248.3% · α +232.7%
2023-09-01
window closed
⚠ CONFLICTING IDEA ON THE SAME TICKER — the board is arguing with itself; net it before trading (ticker view →)
NVDA · Nvidia risk: special-purpose silicon + Huawei SHORT DORMANT 10.4

also touching these tickers, same direction: AI compute capex supercycle has 12-24 months of runway 87 (NVDA) · AI compute capex supercycle has 12-24 months of runway 87 (SMH) · Nvidia + Hugging Face makes NVDA the open-source AI champion 58 (NVDA) · Nvidia + Hugging Face makes NVDA the open-source AI champion 58 (SMH) · DRAM/HBM: the bottleneck that matters 45 (SMH)

⚖ Why this verdict

fully deterministic — evaluate.py replays this from daily closes; nothing below is editable or hand-set

  1. Window: 2022-09-01 → 2023-09-01 — first mention + 12-month horizon, then the window locks.
  2. The call: ▲ LONG NVDA (primary play). NVDA rose 248.3% over the window → direction-adjusted R = +248.3% (the call made money).
  3. Benchmark: holding SPY over the same window returned +15.7%α = +248.3 − (+15.7) = +232.7% — what this call made or lost against just owning the index. This is the number the verdict uses.
  4. Rule fired:
    ▶ HIT — R ≥ +10% AND α ≥ +5 ✓ (R 248.3, α 232.7)
    · PARTIAL — R ≥ +5% OR α ≥ 0
    · MISS — everything else
  5. Credit: supporters of a HIT earn 1.0 each, opposers the inverse — this feeds the scoreboard weights. supported: Brad Gerstner, Chamath, Friedberg, Sacks | opposed: Jason

Conviction timeline

bands: green ≥ 65 · watch ≥ 45 · ember ≥ 15

Plays vs SPY · % since first mention (2022-09-01)

Plays

expressionsymbolkindrelevancerationale
▲ LONG NVDAstock PRIMARY the GPU franchise Chamath's 'Moore's law shifted to GPUs' claim is literally about
▲ LONG AMDstock adjacent second merchant accelerator supplier, levered to the same parallel-compute shift
▲ LONG SMHetf adjacent semiconductor complex captures the compute-demand shift without single-name risk

Mention log

Chamath
Chamath tech w=0.90 · n=83 · E94 (2022-09-01) · explicit_prediction · strength 2 ▶ 35:49 SUPPORT
“the way that he described it to me, which is so true the minute he said it, I was like, my gosh, it's like Moore's law never ended, it just shifted to GPUs. Because the inherent lack of parallelization that CPUs have, you solve the GPUs. And so that's why the surface area of compute of innovation has actually shifted, Jason, to what you're saying, which is all of these new kinds of machine-learned models, because you can just now brute force and create such a tonnage of compute capabilities and resources to solve these problems that weren't possible before.”
Jason
Jason tech w=1.05 · n=56 · E94 (2022-09-01) · sentiment · strength 2 ▶ 37:53 SUPPORT
“You look at the data sets that are available to train. So you have the GPUs still escalating massively the amount of computer power can do. You have cloud computing at the same time, and then you have these data sets.”
Chamath
Chamath tech w=0.90 · n=83 · E99 (2022-10-07) · explicit_prediction · strength 3 ▶ 38:50 SUPPORT
“So this is just an observation that I think that we are continuing to compound knowledge and intelligence effectively at the same rate as Moore's Law and we will continue to be able to do that because this makes it a problem of power and a problem of money. So as long as you can buy enough GPUs from Nvidia or build your own, and as long as you can get access to enough power to run those computers, there really isn't many problems you can't solve.”
Chamath
Chamath tech w=0.90 · n=83 · E103 (2022-11-05) · positioning · strength 3 ▶ 1:25:48 SUPPORT
“One is that the marginal cost of energy goes to zero, and the second is that the marginal cost of compute goes to zero. And the second one is really about shifting compute to more parallelism on GPUs and ASICs and FPGAs. But that's why all of this stuff is possible.”
Chamath
Chamath tech w=0.90 · n=83 · E106 (2022-12-03) · positioning · strength 2 ▶ 1:39:02 SUPPORT
“We sell a lot of machine learning hardware into this market. The biggest buyers are the US government and these ultra high frequency trading organizations.”
Chamath
Chamath tech w=0.90 · n=83 · E111 (2023-01-13) · positioning · strength 1 ▶ 42:50 SUPPORT
“Well, we were building silicon for machine learning. That's different.”
Chamath
Chamath tech w=0.90 · n=83 · E115 (2023-02-11) · explicit_prediction · strength 2 ▶ 41:23 SUPPORT
“The ability to run this at scale is going to happen because we're getting better and better at creating silicon that specializes in doing things in a massively parallelized way and the cost of energy at the same time is getting cheaper and cheaper along with it.”
Chamath
Chamath tech w=0.90 · n=83 · E118 (2023-03-03) · explicit_prediction · strength 3 ▶ 17:57 SUPPORT
“I think it's at the silicon layer, because you need to really re-architect how compute will actually work in a world of all of these models. Those folks will get paid. If you look at AMD and Nvidia, they've been getting paid for years.”
Chamath
Chamath tech w=0.90 · n=83 · E124 (2023-04-14) · explicit_prediction · strength 2 ▶ 56:49 SUPPORT · horizon 6mo
“And six months from now when you're compounding at 48 or 72 hours is like 10 to 12 years in other technology solutions.”
Friedberg
Friedberg tech w=1.08 · n=65 · E130 (2023-05-26) · explicit_prediction · strength 3 ▶ 58:32 SUPPORT
“Well, I mean, I was talking with the CEO and CFO of a major data center REIT, and they shared with me that they're seeing more demand in the last couple of months than they've seen in the prior 10 years.”
Jason
Jason tech w=1.05 · n=56 · E130 (2023-05-26) · explicit_prediction · strength 3 ▶ 59:51 SUPPORT · horizon 120mo
“And I think this is the great renewal for America, another amazing American company. It's only three decades old. It's best years, it's best decades are in front of it, obviously.”
Sacks
Sacks tech w=0.77 · n=53 · E130 (2023-05-26) · sentiment · strength 2 ▶ 1:00:41 SUPPORT
“Yeah, Nvidia has basically joined the trillion-dollar club now in terms of market cap companies. It's really amazing. I mean, I'm kind of kicking myself because this was the easiest buy ever.”
Chamath
Chamath tech w=0.90 · n=83 · E130 (2023-05-26) · explicit_prediction · strength 2 ▶ 1:01:08 REVERSAL
“But when you look at the valuation of the business, they are currently trading at 70 times the next 12 months EBITDA. So how do you think about valuation, even at a trillion dollar market cap, at a trillion dollar market cap, they're trading at 70 times next 12 months EBITDA.”
Chamath
Chamath tech w=0.90 · n=83 · E131 (2023-06-02) · explicit_prediction · strength 3 ▶ 1:22:41 REVERSAL · horizon 6mo
“So I think what I'm waiting for, Friedberg, is like in the next two quarters, if AMD, Facebook, Google, Microsoft and Amazon don't announce something substantive, there's a very good chance that Nvidia runs away with this.”
Jason
Jason tech w=1.05 · n=56 · E131 (2023-06-02) · sentiment · strength 2 ▶ 1:24:54 OPPOSE
“So that could flip where the demand could actually decrease because of software efficiencies or hitting some benchmark that's reasonable enough.”
Friedberg
Friedberg tech w=1.08 · n=65 · E131 (2023-06-02) · sentiment · strength 2 ▶ 1:25:35 SUPPORT
“Look, I think as performance improves, as cost declines, like any economic model, there's a pretty nonlinear relationship with demand. So we'll find new ways to apply this technology. I think the demand is only going to go nonlinear.”
Chamath
Chamath tech w=0.90 · n=83 · E132 (2023-06-10) · positioning · strength 3 ▶ 1:30:44 SUPPORT
“I've told this story before, but I pinged those guys and I was basically like, I just wanna meet the team that built the TPU. Long story short, a year later, I put them in business. And we've been building silicon for this moment for years.”
Brad Gerstner
Brad Gerstner (regular guest ×1.0) tech w=1.41 · n=17 · E133 (2023-06-16) · positioning · strength 3 ▶ 17:52 SUPPORT
“I don't think there's any problems with NVIDIA. I think they're going to continue to perform. I think they'll beat their numbers for the balance of the year.”
Friedberg
Friedberg tech w=1.08 · n=65 · E133 (2023-06-16) · sentiment · strength 2 ▶ 22:37 SUPPORT
“Certainly the most obvious is demand for chips because all this infrastructure is being built out.”
Chamath
Chamath tech w=0.90 · n=83 · E133 (2023-06-16) · explicit_prediction · strength 3 ▶ 1:17:40 SUPPORT
“My God, these people that put the money in the seed round should have just bought NVIDIA. Buy some call options so you can make more money.”
Sacks
Sacks tech w=0.77 · n=53 · E135 (2023-07-01) · explicit_prediction · strength 2 ▶ 54:21 SUPPORT · horizon 24mo
“We have a GPU shortage, and it's probably not going to get better for a year or two, if that.”
Chamath
Chamath tech w=0.90 · n=83 · E135 (2023-07-01) · sentiment · strength 2 ▶ 1:01:48 SUPPORT
“the list price of an H100 is about 30,000, but the street price, so it's very hard to get it. So if you go to eBay and try to buy an H100, it's like 40 or 45,000.”

Who built this conviction

each voice's total force on the score — supports and opposes from every mention, weighted exactly as the replay applied them · share = % of all mention-driven movement

Chamath
Chamath w=0.90
13 scoring events · 60% of moves
+106.4 / -58.2 → net +48.2
Friedberg
Friedberg w=1.08
3 scoring events · 14% of moves
+37.3 → net +37.3
Jason
Jason w=1.05
3 scoring events · 13% of moves
+23.2 / -12.6 → net +10.6
Brad Gerstner
Brad Gerstner w=1.41 regular guest ×1.0
1 scoring event · 9% of moves
+25.6 → net +25.6
Sacks
Sacks w=0.77
2 scoring events · 3% of moves
+8.9 → net +8.9

⏳ decay drained -76.0 over the idea's life — that's time passing, attributed to no one

Score events

episodekindΔafternote
E94 2022-09-01 init +31.6 31.6 E94 born by Chamath (explicit_prediction x2) [w=0.90]
E94 2022-09-01 reinforce +16.2 47.8 E94 Jason support x2 (new voice) [w=1.05]
E95 2022-09-10 decay -1.9 45.9 E95 silent
E96 2022-09-17 decay -1.8 44.1 E96 silent
E97 2022-09-23 decay -1.8 42.3 E97 silent
E98 2022-10-01 decay -1.7 40.6 E98 silent
E99 2022-10-07 reinforce +9.7 50.3 E99 Chamath support x3 [w=0.90]
E100 2022-10-14 decay -2.0 48.3 E100 silent
E101 2022-10-22 decay -1.9 46.3 E101 silent
E102 2022-10-29 decay -1.9 44.5 E102 silent
E103 2022-11-05 reinforce +9.0 53.5 E103 Chamath support x3 [w=0.90]
E105 2022-11-19 decay -2.1 51.4 E105 silent
E106 2022-12-03 reinforce +6.6 58.0 E106 Chamath support x2 [w=0.90]
E107 2022-12-10 decay -2.3 55.6 E107 silent
E108 2022-12-16 decay -2.2 53.4 E108 silent
E109 2022-12-24 decay -2.1 51.3 E109 silent
E110 2023-01-06 decay -2.1 49.2 E110 silent
E111 2023-01-13 reinforce +5.5 54.7 E111 Chamath support x1 [w=0.90]
E112 2023-01-20 decay -2.2 52.5 E112 silent
E113 2023-01-27 decay -2.1 50.4 E113 silent
E114 2023-02-04 decay -2.0 48.4 E114 silent
E115 2023-02-11 reinforce +7.0 55.4 E115 Chamath support x2 [w=0.90]
E116 2023-02-17 decay -2.2 53.2 E116 silent
E118 2023-03-03 reinforce +7.6 60.8 E118 Chamath support x3 [w=0.90]
E119 2023-03-11 decay -2.4 58.4 E119 silent
E120 2023-03-17 decay -2.3 56.0 E120 silent
E121 2023-03-24 decay -2.2 53.8 E121 silent
E122 2023-03-31 decay -2.2 51.7 E122 silent
E123 2023-04-07 decay -2.1 49.6 E123 silent
E124 2023-04-14 reinforce +6.8 56.4 E124 Chamath support x2 [w=0.90]
E125 2023-04-21 decay -2.3 54.2 E125 silent
E126 2023-04-28 decay -2.2 52.0 E126 silent
E128 2023-05-12 decay -2.1 49.9 E128 silent
E129 2023-05-19 decay -2.0 47.9 E129 silent
E130 2023-05-26 reinforce +15.1 63.1 E130 Friedberg support x3 (new voice) [w=1.08]
E130 2023-05-26 reinforce +7.0 70.1 E130 Jason support x3 [w=1.05]
E130 2023-05-26 reinforce +5.2 75.3 E130 Sacks support x2 (new voice) [w=0.77]
E130 2023-05-26 reversal -45.2 30.1 E130 Chamath flips
E131 2023-06-02 oppose -13.0 17.1 E131 Chamath opposes x3 (marked reversal; no prior support to flip) [w=0.90]
E131 2023-06-02 oppose -12.6 4.5 E131 Jason opposes x2 [w=1.05]
E131 2023-06-02 reinforce +15.4 19.9 E131 Friedberg support x2 [w=1.08]
E132 2023-06-10 reinforce +13.0 32.9 E132 Chamath support x3 (flipped from reversal) [w=0.90]
E133 2023-06-16 reinforce +25.6 58.5 E133 Brad Gerstner support x3 (new voice) [w=1.41]
E133 2023-06-16 reinforce +6.7 65.2 E133 Friedberg support x2 [w=1.08]
E133 2023-06-16 reinforce +5.7 70.9 E133 Chamath support x3 [w=0.90]
E134 2023-06-24 decay -2.8 68.0 E134 silent
E135 2023-07-01 reinforce +3.7 71.7 E135 Sacks support x2 [w=0.77]
E135 2023-07-01 reinforce +3.8 75.6 E135 Chamath support x2 [w=0.90]
E136 2023-07-09 decay -3.0 72.5 E136 silent
E137 2023-07-14 decay -2.9 69.6 E137 silent
E139 2023-07-27 decay -2.8 66.9 E139 silent
E140 2023-08-04 decay -2.7 64.2 E140 silent
E141 2023-08-11 decay -2.6 61.6 E141 silent
E142 2023-08-18 decay -2.5 59.1 E142 silent
E143 2023-08-25 decay -2.4 56.8 E143 silent
E144 2023-09-01 decay -2.3 54.5 E144 silent