EnergySavvy

Energy Professional. Advocate Sustainable Development & Energy for all. Digital Transformation,AI,Renewables, Climate Change Mitigation & CCUS Enthusiast

[Sanjeev Sanyal @sanjeevsanyal]

Why we should never create a fully interconnected system - and certainly not one run by AI

[Chamath Palihapitiya @chamath]

You should expect the silicon chip companies to move up the stack as the application companies move down the stack.

In AI, it is increasingly true that everyone competes with everyone. Everyone will soon offer their own LPS, silicon, cloud and applications.

The question is what will the constraint be that you can build a long term market and margins around…

Is it distribution? Is it a data moat? Is it a physical constraint like power?

[Javier Blas @JavierBlas]

OIL PIPELINEs GEOPOLITICS: Saudi Arabia has announced plans today to expand its key East-West pipeline (bypassing the Strait of Hormuz), which has a nominal capacity of 7m b/d (although currently is running probably at around 6m b/d after an attack destroyed a pumping station in September).

In the next 7-8 weeks, Saudi Aramco would be able to boost capacity by 1.2m b/d using an existing natural gas pipe, making changes to ship crude. Riyadh didn't disclose further details, other than the line would need to revert to nat gas by May as the kingdom needs it to feed power stations during the summer months.

[My hypothesis is this could be the old 48-inches, ~1,500-km long IPSA (Iraqi Pipeline in Saudi Arabia) built in the 1980s which runs largely parallel to the East-West pipeline from pumping station #3 all the way to near Yanbu. The pipeline was seized by the Saudis after Saddam Hussein invaded Kuwait in Aug 1990 and later it was repurposed for use in the country's Master Gas System]

More long-term, Saudi officials said they plan to boost shipping capacity of the East-West pipeline to ~10m b/d in the next 2-3 years, mostly improving pumping capacity (rather than building another pipe).

For more on the East-West pipeline, I wrote this @Opinion column early on the conflict: https://t.co/4xlOFVnJxf

[Seneca the Younger @SenecaQuote]

"If a man knows not to which port he sails, no wind is favorable."

[Assaad Razzouk @AssaadRazzouk]

China vs everyone else, in 2 numbers:
>Industrial robots installed: China 354,000 v. Rest of the world combined: 249,000. China is 59% of the global total (and I don't even want to think about 2026 data when it's out, let alone 2030)
>Engineering bachelor’s grads per year: China 1.6m. US + UK + EU combined: 30% of that

The factory of the future is being built, and staffed, in one country. Meanwhile, so many seem to just want to talk about, and do, fossil fuel wars

[Andrej Karpathy @karpathy]

Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.

- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.

The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.

So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

[The Data of Everything @TheDataHubX]

Which Sectors Contribute the Most to the World's Largest Economies?

1. United States
Services: 79.7%
Industry: 17.3%
Agriculture: 0.9%

2. China
Services: 56.8%
Industry: 36.4%
Agriculture: 6.8%

3. Germany
Services: 64.0%
Industry: 25.6%
Agriculture: 0.9%

4. Japan
Services: 71.4%
Industry: 26.8%
Agriculture: 1.0%

5. India
Services: 48.0%
Industry: 25.2%
Agriculture: 17.6%

6. United Kingdom
Services: 72.8%
Industry: 16.7%
Agriculture: 0.6%

7. France
Services: 70.9%
Industry: 17.2%
Agriculture: 1.3%

8. Italy
Services: 64.7%
Industry: 22.7%
Agriculture: 2.0%

9. Russia
Services: 57.7%
Industry: 31.4%
Agriculture: 2.9%

10. Brazil
Services: 59.2%
Industry: 20.9%
Agriculture: 5.8%

11. Canada
Services: 64.1%
Industry: 27.4%
Agriculture: 1.9%

12. Mexico
Services: 58.6%
Industry: 31.0%
Agriculture: 3.9%

13. Spain
Services: 68.9%
Industry: 19.5%
Agriculture: 2.8%

14. South Korea
Services: 57.5%
Industry: 33.9%
Agriculture: 1.5%

15. Australia
Services: 66.1%
Industry: 25.5%
Agriculture: 2.0%

Sources: World Bank (World Development Indicators, 2024), U.S. Bureau of Economic Analysis (BEA),CIA World Factbook.

[Prasanna Viswanathan @prasannavishy]

$2.9 trillion. That is how much Big Tech has committed to the AI buildout off its balance sheets. Against just $126 billion in net cash.

For instance, Meta’s $27 billion Hyperion data centre sits in an entity that is 80% owned by Blue Owl. Meta says it isn’t the primary beneficiary, so the entity stays off its books. Yet Meta carries a $28 billion residual value guarantee, and its auditor EY flagged the call as a critical audit matter.

Oracle’s Project Jupiter runs through a web of developers, a 20-bank construction loan and leasebacks, keeping the debt off Oracle’s books while Oracle stays on the hook for the lease. via @businessline

[The Kobeissi Letter @KobeissiLetter]

BREAKING: President Trump says Russia and Ukraine have agreed to an “energy ceasefire” with immediate effect.

[Javier Blas @JavierBlas]

Ahead of a meeting on Oct 15, IEA head Fatih Birol urge member countries to weigh additional releases of diesel from the strategic petroleum reserves

[Velina Tchakarova @vtchakarova]

The Collectivists and Constructivists took over Germany and that’s the outcome now.

[Gaurav Sen @gkcs_]

OpenAI breached Hugging Face's production servers.

This video summarizes its incident report.

Incident: https://t.co/96EZoyDwtq
AI System Design Cohort: https://t.co/6l1xVg3h9v

[Jaydeep @_jaydeepkarale]

Average AI Conversations in Most Companies

Tech Manager: I'm excited to share that we're officially pivoting to an AI-first operating model. We're going to leverage agentic AI to unlock enterprise value at scale.

Executive: What are we using AI for?

Tech Manager: That's what we're here to determine.

Executive: So, we don't know?

Tech Manager: We're currently in use case discovery.

Executive: Then why are we AI-first?

Tech Manager: Because AI-first organizations don't wait for use cases.

Executive: What do they do?

Tech Manager: They accelerate them.

Executive: Accelerate what?

Tech Manager: The use cases.

Executive: The ones we don't have?

Tech Manager: Yet.

Executive: Okay. What does AI actually do?

Tech Manager: It augments human intelligence through a human-in-the-loop framework while democratizing access to enterprise knowledge.

Executive: What does that mean?

Tech Manager: Copilot.

Executive: For what?

Tech Manager: Everything.

Executive: Can it fix our inventory problem?

Tech Manager: Not directly.

Executive: Can it fix our order backlog?

Tech Manager: Not currently.

Executive: Can it clean up our customer data?

Tech Manager: The data will require remediation before AI can assume responsibility for it.

Executive: So before AI can fix our problems, we have to fix our own problems?

Tech Manager: Exactly. That's what makes AI transformational.

Executive: How much is this going to cost?

Tech Manager: We're still developing the value realization framework.

Executive: So you don't know?

Tech Manager: We're taking an outcomes-based approach.

Executive: What's the outcome?

Tech Manager: AI readiness.

Executive: And what do we get when we're AI-ready?

Tech Manager: We'll be ready for AI.

Executive: Did we hire you to develop an AI strategy or sell us AI?

Tech Manager: Great question. I think we should schedule an AI strategy workshop to really unpack that one.

Executive: Isn't this the AI strategy workshop?

Tech Manager: Uh, this is the AI strategy alignment workshop. Would you like me to schedule a meeting to discuss?

Executive: No, thank you.

[Satya Nadella @satyanadella]

https://t.co/MjwFy73LOF

[Anas Alhajji @anasalhajji]

🔷It hasn’t even been a month since President Trump signed the Graham sanctions on Russia into law.

🔷Graham’s supporters were bragging about the respect he’d earned and how destructive those sanctions would be for Russia. What now?

🔷The irony is that I recently wrote Trump might reach some kind of temporary deal with Iran to ease prices—it turned out to be with Russia instead. That said, a temporary agreement with Iran is still possible.

🔷When Zelensky offered a peace plan with Russia a few years ago, the EU rejected it and pushed for war. I said then that the West was willing to fight Russia to the last Ukrainian. Some people got angry at me for saying it. Again—what now? What about the revenues Putin will collect? For what? Just to lower diesel prices a few cents while Ukrainians keep dying.

🔷Three weeks ago I said the Graham Act was symbolic and would have no real impact on the ground. Reality has now proven that point.

[Nikesh Arora @nikesharora]

@satyanadella extremely well put. I have been saying this, not as elegantly - we cannot rely on the disclosures of frontier LLMs alone:
1. These harnesses need to be constructed so that third parties can get involved in observability and transparency..
2. As we get there we also can imagine users (enterprises) wanting to adapt the guardrails to their values, principles and business practices. One cannot imagine a global set of guardrails owned by the model creators.
3. No real business will be able to implement the enhanced capabilites of models if they remain black boxes, auditability, verification and compliance are essential premises to ensure that businesses can continue to operate showing duty of care.
4. Information securty architectures are consistent over decades, the AI architectures need to make room for us to be able to interface seamlessly, at speed and consistently - today all attempts by us are jerry rigged and band aids because we are trying to adapt to the speed of the model providers. If the AI industry doesn't support the simultaneous capability of the security industry things will stall.
5. To foster the diffusion of AI at speed and build trust we need to have momentum behind the conversation just initiated by Satya.

[a16z @a16z]

"Energy Capacity = Economic Capacity"

Former Intel CEO Pat Gelsinger on why America's power grid is the ceiling on growth:

"We went through 10 to 15 years where essentially I was taking coal offline at the rate I was adding renewables, and essentially the nation was flatlined in terms of overall energy capacity."

"So essentially our economic capacity as a nation, flat for fifteen years."

"Even with that, we've gone to maybe increasing our national energy capacity 4% per year. Going from essentially zero to one."

"Nuclear as base load is a fabulous thing that we want to go build more of. Unfortunately all of our renewables have deep dependencies in China."

"Energy capacity somewhat dampens how euphoric we can get on AI. Why build a new data center and buy the million GPUs if I can't power them?"

@PGelsinger @RaghuRaghuram @appenz

[a16z @a16z]

TypeSafe AI's Diogo Almeida on why Jev is called Jev, and what cheap intelligence finally changes about software:

"It's wild that AI is so cool and software has been unchanged in 10 years... The most we can do is add a little chatbot in the side sometimes that can take actions, but not all actions."

"TypeSafe is making AI for software. We want to make AI powerful, not just for humans in the loop, but to actually build real software."

"It's about the laziness to spend 10 hours to do the five-minute task instantly and to never have to do it again. It should be an ROI decision for people who automate stuff. I would just like it to be automatable."

"I think that people will just make new kinds of work, hence the Jev in Jevons. New kinds of work once that stuff is doable."

"As we have lots of intelligence at lots of different cost and speed trade-offs, the super systems-y types will be making trade-offs. Jev's gonna be 1000x too smart for them. They just want an approximate guess to optimistically route here and there."

Martin Casado: "The good news is we get to rebuild systems again. We have a new primitive. It's kind of a new way of thinking about doing software."

@CompleteSkeptic @typesafeai @bhorowitz @martin_casado

[a16z @a16z]

Token prices keep falling and GPU rental prices keep rising

Intelligence gets cheaper, usage goes up, and a model ends up in every piece of software

[a16z @a16z]

Call center jobs grew ~4% annually for 15 years

Now they’re shrinking 4% annually

Charts of the Week: https://t.co/6UOlZZPpiE