Brandon Gleklen

@BatteryVentures views are my own, no investment advice intended.

[Brandon Gleklen @BrandonGleklen]

https://t.co/ppMrJMJ3PU

[Brandon Gleklen @BrandonGleklen]

@DBCJason @dlee4three @thehwcollectlve Are you going to continue publishing dynasty basketball rankings?

[Brandon Gleklen @BrandonGleklen]

A thought experiment I’ve been using recently:

If all Anthropic employees worked at your customer/prospect, and focused on your use case, would they still pay for your product?

(I think many startups pass this bar.)

[Brandon Gleklen @BrandonGleklen]

Competence as Tragedy: https://t.co/otsSg2uC46

[Tomás (at less.online) Bjartur @BjarturTomas]

Mathematician reacts to OpenAI's recent proof:

[Brandon Gleklen @BrandonGleklen]

Excited to be working with Sarim, Raj and team alongside our friends at @lightspeedvp and @NexusVP to change cancer care for the better!

[Brandon Gleklen @BrandonGleklen]

Excited for @BatteryVentures to lead the $22M round for @Triomicsinc and to join the board.

Oncology is one of the hardest areas to deploy AI due to the complexity of patient records (can be 300+ pages and 80%+ unstructured).

[Brandon Gleklen @BrandonGleklen]

Triomics is using AI to reconstruct the chronology of care and structure the patient record.

We're live at places like MSK, MD Anderson, Yale, Mount Sinai and Texas Oncology, automating workflows ranging from clinical trial matching to registry reporting and visit preparation.

[Brandon Gleklen @BrandonGleklen]

High impact role 👇

Spent a significant amount of time on our board call today talking about what an impact this person will make. Highly recommend working with @Altimor

[Flo Crivello @Altimor]

We're hiring our first Growth Product Manager at Lindy.

Lindy Assistant is growing fast and users positively rave about it — looking for someone to help us beef up the growth engine.

DMs open!

[Brandon Gleklen @BrandonGleklen]

“Application software has never had great moats”

That’s true. But there’s always been a need to procure a solution.

That changing - people self-serving their use cases using Skills, Cowork etc. - is the issue that will impact growth rates more than “undifferentiated tech.”

[Brandon Gleklen @BrandonGleklen]

@SixersAdam This is the best fix: https://t.co/AbMP1PqwBq

[Brandon Gleklen @BrandonGleklen]

@JakobSanderson JCM?

[Brandon Gleklen @BrandonGleklen]

@RileyRalmuto My favorite post on this topic @threepointone https://t.co/SkqcwDaE93

[Brandon Gleklen @BrandonGleklen]

A useful definition of “AI native”:

"Inference is our #1 cost by a lot (more than payroll)"

Maybe not true for every 'AI native company' but any company with this economic profile deserves the moniker.

[Flo Crivello @Altimor]

We've tested new OSS models the moment they're released for a while at Lindy. Inference is our #1 cost by a lot (more than payroll) — cutting it by 2-5x would be transformative.
Last year, OSS models were "not even close."
3 mos ago, "almost there." Came close to making Kimi K2.5 our default.
I think we are right now crossing the line to "at the frontier, for most use cases." GLM-5.1 in particular is incredible and will likely be our default soon.
Surprised by this development — OSS caught up.

[Brandon Gleklen @BrandonGleklen]

This is a small thing but @claudeai can you make it so that voice input is always available in chat on windows desktop?

e.g. if I add files the ability to do voice input for the prompt goes away.

[Brandon Gleklen @BrandonGleklen]

@JaredSleeper TY

[Brandon Gleklen @BrandonGleklen]

@JaredSleeper I think I saw someone make this roundness analogy and you commented on it? I can’t find it but it stuck with me

[Brandon Gleklen @BrandonGleklen]

https://t.co/SGhKNFUZbv

[François Chollet @fchollet]

One of the biggest misconceptions people have about intelligence is seeing it as some kind of unbounded scalar stat, like height. "Future AI will have 10,000 IQ", that sort of thing. Intelligence is a conversion ratio, with an optimality bound. Increasing intelligence is not so much like "making the tower taller", it's more like "making the ball rounder". At some point it's already pretty damn spherical and any improvement is marginal.

Now of course smart humans aren't quite at the optimal bound yet on an individual level, and machines will have many advantages besides intelligence -- mostly the removal of biological bottlenecks: greater processing speed, unlimited working memory, unlimited memory with perfect recall... but these are mostly things humans can also access through externalized cognitive tools.

[Brandon Gleklen @BrandonGleklen]

Intelligence might be not be like “height” and be more like “roundness.” (h/t @fchollet)

You can always make a marble more perfectly round at the microscopic level but does that matter?

To be fair, the Earth is more round than a beach ball, and the global economy is probably Earth-sized.

[Jared Sleeper @JaredSleeper]

At this point, one way or another, super intelligence (at least domain by domain) seems like a given on any reasonable investment horizon. Might not happen, might be something we're missing, but it is hard to bet against it.

So the real investment question is not about the production function for intelligence per se, it is about the demand function.

Maxi case: Demand for intelligence is virtually infinite. The smarter the models get, the more we'll demand them. This applies to almost every conceivable domain, so the frontier model vendors will enjoy the same clear advantages they have in code as oligopolistic suppliers of a permanently capacity-constrained resource (frontier intelligence). Mankind will colonize planets, build mass solar arrays around the sun, apply intelligence with stunning ubiquity and completeness to manipulate our bodies, world, etc. Robotics will improve to the point where intelligence is embedded in the physical world, drawing massive compute. A true singularity + abundance scenario. Hard not to root for, except for the disruption on the way.

Mini case: Demand for intelligence is capped in most domains. Humans evolved to have give or take the intelligence we "need" to operate on Earth/socially and we're limited in how much intelligence we can consume from external sources As a result, models will exceed the intelligence consumption capacity and/or requirement of the typical worker/consumer in 2-3 years, open source models will follow up shortly and the cost of intelligence will collapse to zero as the models get 100x more efficient in the years to come. Vendors with distribution (whether legacy or AI native) will seamlessly add intelligence to their products (the AI will help!). Much like electricity and the internet, intelligence will be something we take for granted as a feature of society, rarely think about and a commodity priced to input + distribution costs (energy, silicon, etc.).

Of course, there are many, many cases in between- but the marginal question has clearly shifted from "is AGI/ASI possible" to "what are the implications once it is here."

Current thinking is that this varies by domain- in some (customer support, certain enterprise agent applications) we're already arguably close to the intellectual horsepower required and we're seeing some companies start to migrate from frontier to frontier-y self-built models.

In others (coding, strategy, hedge fund trading, etc.) we remain far, far away.

In many others, we still lack the context to actually know exactly where we stand.

[Brandon Gleklen @BrandonGleklen]

@jasonlk This is really good - it’s ironic that as AI gets better and automates more, hiring the right people gets harder

[Brandon Gleklen @BrandonGleklen]

@pmmbasketball Still that high on JDub after this year?

[Brandon Gleklen @BrandonGleklen]

@doodlestein 100%. The default skill-creator skill is super limiting and holds back a lot of its power, wrote about that here:

https://t.co/2p1QBYZ9fO

[Brandon Gleklen @BrandonGleklen]

https://t.co/ppMrJMJ3PU