David Timis (@DavidTimis) header
David Timis (@DavidTimis) profile picture

Global Communications & Public Affairs Manager @YouEmployed | Global Shaper @BrusselShapers | Alumnus @UofGlasgow and @collegeofeurope

Brussels, Belgium
Joined November 2011
Photo by David Timis (@DavidTimis)Photo by David Timis (@DavidTimis)Photo by David Timis (@DavidTimis)Photo by David Timis (@DavidTimis)Photo by David Timis (@DavidTimis)Photo by David Timis (@DavidTimis)Photo by David Timis (@DavidTimis)Photo by David Timis (@DavidTimis)Photo by David Timis (@DavidTimis)Photo by David Timis (@DavidTimis)
"Rare are those people who use the mind; few use the heart; and really unique are those who use both." - Rita Levi-Montalcini
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SpaceX may own 16% of all world’s AI compute by end 2027. I’d bet it’s just the beginning.
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David Timis retweeted
Bank of America: "The 90s dot-com bust was excess capacity chasing insufficient demand; AI may be structurally opposite: abundant demand chasing scarce compute."
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David Timis retweeted
JP Morgan initiation on $PLTR
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Palantir's Net Retention Rate has now accelerated for 12 straight quarters... One of one. $PLTR
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David Timis retweeted
PALANTIR SHOWS FINE-TUNED NVIDIA 4B AI MODEL BEATING GPT-6 ASTRA & CLAUDE SONNET 5.5 AT A FRACTION OF THE COST In its Q3 business update, $PLTR revealed that a fine-tuned $NVDA Nemotron 3 Nano model with just 4 billion parameters outperformed much larger frontier models on a real-world customer task. The results, based on classifying requests for information for construction firm McCarthy: • NVIDIA Nemotron 4B: ~75% accuracy at $0.10 per million tokens. • Claude Sonnet 5.5: ~66% accuracy at $4 per million tokens. • GPT-6 Astra: ~62% accuracy at $20 per million tokens. Palantir says the fine-tuned models are expected to save McCarthy approximately 30,000 drafting hours annually. Separately, NVIDIA itself is now training open AI models on its own supply chain data inside Palantir's Ontology, spanning millions of parts and thousands of suppliers. Jensen Huang says the partnership combines NVIDIA's Nemotron models with Palantir's Ontology to: “Reason, plan and orchestrate the journey from wafer to token.”
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David Timis retweeted
First take on $AAPL (stock flat). Business overall is solid despite navigating higher memory costs and higher prices to consumers. Sept guidance in 45 mins. 1. iPhone was up 17.5% vs. Street at up 15.5%. Rock solid. 2. Mac got a 22% price increase for the full quarter and beat estimates. Sales up 24% yy, compared to Street looking for up 15%. Shows how much Mac bucked the Intel announcement for a slowdown in consumer we say last week. 3. iPad got a 21% price increase and missed. Sept was down 10% yy vs. Street at flat. For December, Street is at down 3%. They should beat that with the new models just announced. 4. Gross margin, adjusting for tariff refund was 46.9% vs. Street at 47.5%. Shows the price increase is not offsetting memory costs. 5. Services were in line up 10%, compared to up 12% in June. 6. Wearables down 8% vs. Street at down 4%. I dont know what to make of this.
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Hyperscaler CDS are breaking out to new highs. This is bad news for neoclouds, particularly for $CRWV. Investors will be asking for higher interest rates to fund hyperscaler data center projects, which leads to even higher rates for neoclouds.
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2027 is shaping up to be biggest step change in AI power density yet: • $NVDA Rubin Ultra ~500kW per rack • $AMD MI500 ~1,000kW per rack • $AMZN Trainium4 ~330kW per rack • $GOOGL TPU v9 ~200kW per rack Traditional data centers were built for CPU racks of just ~10kW so this shift will require a lot of upgrades to existing facilities and fundamentally different electrical and liquid cooling systems in new builds.
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David Timis retweeted
on spaceX vs Tesla very crudely: robotaxi is a bigger opportunity than starlink but orbital compute is a *much* bigger opportunity than robotaxi and optimus requires more baking time than orbital compute and Optimus's success is predicated on access to gobsmacking amounts of superintelligence On our modeling, compared against the no merger case, even if merged at the current share price ratio Tesla shareholders would be ~1.6x better off in 2031 while SpaceX shareholders would be ~2x better off. On a longer timeframe (2036) Tesla shareholders would be ~5x better off having merged whereas SpaceX shareholders should be more indifferent ~1.3x better off. So the fair premium depends heavily on your timeframe. On longer time horizons SpaceX shareholders should be asking for a discount. On shorter time horizons Tesla shareholders should be asking for a premium. But everyone is better off with a merged entity. A 30% premium paid on Tesla's share price to day would effectively split the difference on the 2031 time frame; Tesla acquired at a 50% discount would equilibreate return differentials on the 2036 time horizon.
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Of the $1+ trillion companies, Tesla $TSLA and SpaceX $SPCX have been the two best performers over the last three months. Tesla $TSLA up 32.2% SpaceX $SPCX up 29.9%
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Forward P/E of the most popular stocks
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Tesla just had a HUGE month in Europe! Almost every country that has reported October vehicle registration so far is up big for $TSLA The standout is Norway. Tesla had its best October on record there and finished as the #1 brand with 9.8% share, just 55 cars ahead of Toyota And it did that in a month where Chinese brands hit a record 22.5% of new cars in Norway Germany, Italy and the UK are the big ones though, and they have yet to report FSD is being approved across the continent and should drive further Tesla purchases heading into 2027 as the expected full approval happens
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Die trying to get to the frontier, or live long enough to serve inference. The story of @MistralAI and other labs that are not at the frontier.
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David Timis retweeted
$ORCL will have a load of ASICs in their cloud (Deutsche) Obviously negative for $NVDA as the market is clearly fragmenting with TPUs and other ASICs now seeing clear momentum
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What matters is the portfolio. The ideas. The content. The people we have impacted positively. The stuff we have built.
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We should take a look at our LinkedIn Profile. Revisit our resume. Ask Chat GPT, Claude and Gemini to create our obituaries or answer if we are any good or tell us what work we are associated with. Are the results a bunch of titles and roles and company names?
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Start building ourselves and not just our company or brand. Start growing our possibilities not just growing the possibilities for those who pay us. This is not a zero sum game. The better we are and the more we grow, the better for the company and the clients we work for.
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Ask if we were separated from our company brand or our budget would people still call us? Are we only building value for others and leasing value from their budgets or are we also building value for ourselves?
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