Spencer Wolf

#Author of AFTER MIND. Futurist, visionary #AI novel with utterly human characters.

[Spencer Wolf @SpencerWolfAuth]

@ICannot_Enough @Tesla Honest question: In these stats, is Autopilot FSD? Or, if Autopilot features are always on in the background (emergency braking, lane warnings, etc.), how do you drive a Tesla without Autopilot?

Thanks, James!

[Spencer Wolf @SpencerWolfAuth]

@chamath Hypothesis: every child builds a sandcastle at the beach starting with a pyramid. It's a natural, strong foundation. ... which holds true around the world, all time periods. Evolve that foundation up from first principles and the Pyramids arise.

[Spencer Wolf @SpencerWolfAuth]

@chamath Chamath, for your new venture - potentially two solutions in one: plastic eating bacteria and pharmaceuticals.

Like adding water purification tablets... just add modified bacteria to clear the microplastics. @chamath

https://t.co/KEuU3MbSaZ

[Spencer Wolf @SpencerWolfAuth]

@TheOneAndArjun @s_r_x_9 @pietertypes @chrisbcore @SpencerWolfAuth

[Spencer Wolf @SpencerWolfAuth]

@TheOneAndArjun @s_r_x_9 @pietertypes @chrisbcore private set score for SpencerWolfAuth? Grok and I had fun trying different approaches.

[David Sinclair @davidasinclair]

If epigenetic noise isn’t a driver of aging & mutations are, then reprogramming by OSK shouldn’t:

1. Increase mouse health & lifespan
2. Be thwarted by inhibiting epigenome-modifying enzymes
3. Reverse blindness in old mice

…because mutations are permanent.
But yet it does

[Alex Zhavoronkov, PhD (aka Aleksandrs Zavoronkovs) @biogerontology]

Very interesting perspective and underlying paper. I don't have the answer. What do you think?

https://t.co/JyS5rh2yRl

[Spencer Wolf @SpencerWolfAuth]

@skorusARK I remember laser etching on crystal lasts billions of years. Grok confirms it, along with DNA and others.
https://t.co/ll3NZ8qXqK

[Spencer Wolf @SpencerWolfAuth]

@squawksquare @squawksquare You have remarkable trading agility and sense for the reversal price points. What tools do you use? What timeframe on the chart?

[Spencer Wolf @SpencerWolfAuth]

What about a split into $TSLA and $TSLAI. Just like Alphabet’s post-IPO split with the non-voting GOOG class that maintained shareholder $ value, and class A GOOGL that preserved majority control for founders Larry and Sergey.

In Elon’s case, TSLAI would give him voting control over all AI and robotics developed within Tesla.

@MartinViecha @elonmusk

[Spencer Wolf @SpencerWolfAuth]

Cybertruck acceleration is 🔥🤩 Happy Holidays and looking forward to the real deal in ‘24!! ⁦@robmaurer⁩ ⁦@SawyerMerritt⁩

[Gavin Baker @GavinSBaker]

Foundation Models without significant RLHF *and* access to high quality proprietary datasets are likely the fastest depreciating assets in human history.  @ericvishria

I think only four are likely to have enduring value and transition into “Foundation Agents” over the next few years:

ChatGPT, Gemini, Grok/Tesla/X and Llama.

ChatGPT by virtue of RLHF and Microsoft’s various datasets plus access to closed, internal data at most enterprises via CoPilot.  If OpenAI ever separated from Microsoft then its value would asymptote to zero.  OpenAI trying to make both a GPU competitor *and* a phone would be crazy bearish and epic strategic mistake.  Azure OpenAI doing much better than standalone OpenAI on enterprise side.  Enterprise is hard.

Gemini by virtue of RLHF (via the SGE) and Google’s many datasets (Youtube transcripts, gmail).

Grok by virtue of RLHF via inclusion in X’s premium tier and access to X’s real-time data.  Combination of Grok with the visual dataset and v12 algorithm from Tesla will likely create the best AI for robotics and the “real world.”  Likely to see a much better version of RT-2 in Optimus. Could also be an insertion point for Tesla to enter cloud computing as application SaaS is replaced by MaaS (models as a service).

Llama is the only model on the list that is open-source. The one with the widest range of outcomes.  Might be wise to invest more in this and less in the Metaverse in front of the coming humiliation from Apple's headset.  The current virtual personality strategy seems deeply strange, but I am old.  Could rapidly iterate on Llama, put it in Insta/WhatsApp/BigBlue for RLHF, try to compete in search while agentic AI slowly replaces search and then go into cloud computing via Llama (open source but needs to run in our cloud).  Just a thought.

Obviously all four of these will need to be iterated every 12-18 months (GPT v5, etc.) as they are also depreciating.

This isn’t a “Game of Kings.”  This is a “Game of Emperors.”

Amazon trying to enter the game via Anthropic which is a “Crown Prince” at best right now.  Google invested in Anthropic primarily to help TPU ecosystem - Amazon likely needs both the LLM engineering talent (no great internal LLM yet) and to help Trainium ecosystem.  Bedrock good strategy though and P5 is the best H100 instance. Apple is nowhere which is a risk to them - their only potential friend is Grok/Tesla with some shot of Microsoft/OpenAI via a search deal for Bing.  Meta could’ve been a friend, but whoops - ATT sure was fun but a few years later turned out to have been irrelevant and only increased the competitive advantages of the largest apps like Meta.  Exact opposite of what Apple wanted to accomplish.  Possible that if Gemini leads to a dramatically superior assistant vs. Siri then Android starts really gaining share.

Verticalized AI’s like MidJourney will also have value. Maybe a *lot* of value.

Regulatory capture - see @bgurley thoughts - also increases the odds of the outcome described above. As an investor, this is great. As a human, I think some smart regulation is probably wise, but smart regulation is rare. Most important outcome to avoid as a human is a world with only one dominant model. Open source good in this sense.

Key assumption underpinning all of this is that scaling laws will continue (i.e. the loss ratio prediction from the GPT4 technical report) such that “intelligence is an engineering problem.”

If not, then might be a free for all although arguably proprietary data and RLHF would be even more important.

Nvidia is a wild card - they would like more than four dominant Foundation Models in the same way they want more than a few cloud computing providers.  They will be able to impact the outcome in the same way they have given Coreweave and Lamda unnaturally high incremental share of GPU cloud computing revenues this year.  Wonder what the competitive landscape would look like absent Megatron and what they will do next.

[Spencer Wolf @SpencerWolfAuth]

Do you remember when you joined X? I do! #MyXAnniversary

[Tesla Optimus @Tesla_Optimus]

Optimus can now sort objects autonomously 🤖

Its neural network is trained fully end-to-end: video in, controls out.

Come join to help develop Optimus (& improve its yoga routine 🧘)

→ https://t.co/dBhQqg1qya

[Andrew Côté @Andercot]

LK-99 Endgame: What Happens Next & Market Size

If LK-99 is a room-temperature ambient-pressure superconductor, there are three distinct possibilities depending on its eventual engineering properties.

Here is a straightforward explanation of each scenario and estimated total market sizes in ARR:

The two limits on superconductor performance are:
- How much current it can carry
- How much magnetic field it can withstand

If either of these limits are exceeded, superconductors stop working. The scenarios are high/low field and high/low current, but you can't really get high-field without high-current, so only three scenarios

Scenario 1: Low-field, low-current ~$1.5 trn:
LK-99 saturates at relatively low fields, like 0.3T, and relatively low current densities, of ~1 amp / mm^2. It works in delicate electronics, small packages, at high efficiencies, with extremely high sensitivity.

It revolutionizes the following industries:
- Telecom hardware $650 bn; Cellphones $450 bn; Electronic Sensors $200bn; Satellites $70bn; GPUs $40bn; CPUs $20bn; Antennas $20bn.

Scenario 2: Low-field, high-current ~ $2 trn:
LK-99 can carry large current densities, on the order of >1000 amps / mm^2, but can't stand strong magnetic fields. It gains relevance in power transmission, switches, relays, and larger electrical equipment.

It revolutionizes the following industries:
Power transmission $320 bn; Wires + cables $200bn; Switches & Relays ~$ 25 bn and many others.

Scenario 3: High-field, high-current ~ $4.5 trn:
LK-99 can operate in high fields of several Tesla and high currents of >1000 amps / mm^2. It revolutionizes fundamental industries by replacing motors, generators, transportation equipment, and unlocks new energy sources like fusion.

It revolutionizes the following industries:
Power generation $1.8 trn; Electric Motors $300 bn; Rail freight $250 bn; Energy Storage $200 bn

~~~~
Some important considerations:
- "The totals don't add up" - If something works at high field, it works at low-field, and same for current. Therefore Scenario 1 is the base-case and adds to the bottom line of both other scenarios; it places the least engineering requirements on the material. All numbers for total market sizes are estimates found online in popular market reports for ~2022.

- To incorporate this material into micro-electronics means re-thinking the extremely-mature CMOS 300mm silicon wafer fabrication process, a process that would take a decade if not more to get right.

- A final consideration is the mechanical strain the material can withstand, which also affects the current and field tolerances of existing superconductors. Bulk deformations of the crystal lattice can disrupt superconducting properties - this issue has over-time been improved upon in modern high-temperature superconductors but is still present, and may limit applications in the long-run.

- Our current generation of YCBO-based high-temperature superconductors started out as low-field, low-current, highly strain-sensitive, and over 30+ years of engineering development, these now carry >1000 amps/mm^2 in fields as high as 10T (although these numbers trade off against each other). What this means is, with time, engineering, patience, and concerted effort, if TK-99 is a superconductor then Scenario #3 is highly likely within 10-20 years.

~~~~
Conservative estimate:
Current conservative estimates by an MIT professor put the probability of LK-99 being "it" at 5%.

Assuming a long-term achievement of Scenario 3, this gives an expectation value of a $225 billion annual market.
~~~~

Caveat: LK-99 is not yet confirmed to be a superconductor but has several suggestive corroborations from other experimentalists and simulations. I am reserving judgement until results are confirmed by a Department of Energy National Lab in the USA or a similarly regarded institution.

[Spencer Wolf @SpencerWolfAuth]

@Jason @Jason was this you?

[David Sinclair @davidasinclair]

Grateful to share our latest publication: We’ve previously shown age reversal is possible using gene therapy to turn on embryonic genes. Now we show it’s possible with chemical cocktails, a step towards affordable whole-body rejuvenation 1/17 https://t.co/J9c01lv5FQ

[Spencer Wolf @SpencerWolfAuth]

@jpr007 Why does it cost NASA $1 Billion to get two spacesuits?

How much will it cost @SpaceX to make 100 suits for Starship? Sounds like first principles and order of magnitude need to be the first post-it notes up on the design board. 🚀

[Spencer Wolf @SpencerWolfAuth]

I was fortunate to be invited to list my book, After Mind, on @Shepherd_books. Check it out. I created a list of my favorite sci-fi books about survival that even non-sci-fi fans will love. What do you think of this list? Yea or nay? Any others? https://t.co/y7rwmz8kaV