Business Applications & Analytics, Western Digital. Aligning teams to scale. Alum of @Cisco, @ChargePointnet, @Cornell, @KelloggSchool.
Silicon Valley, USA
Joined April 2011
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Mark Homan retweeted
Inside a human brain when reading a book.
Readers added context they thought people might want to know
This video shows time-lapse of cultured neurons connecting via growth cones in a lab dish, not processes in a living human brain while reading. Similar real clips by Dr. Lila Landowski show developmental wiring; this one's exact source is unconfirmed.
youtube.com/watch?v=Rvmvt7…
lifo.gr/now/tech-scien…
Mark Homan retweeted
Every day that I wake up, I am just amazed. I never enjoyed reading the MSM, but with so many developments in AI, health, the environment, robotics, and so much more, I am glad to say:
It's truly the BEST time to be alive!
Mark Homan retweeted
Grok 4.7 is insanely good.
The model is not the bottleneck anymore. I believe harness reliability and everything around it is...
I read almost every comment on my "Week 1 at SpaceXAI" post, and one thing surprised me.
Not many people said "make Grok smarter", but rather make the agents and bots finish the work 😅
> don't stop halfway through
> don't lose the browser
> don't forget what you're doing
> don't get stuck and wait for me to notice
That's actually a great problem to have. People are already using Grok for real work (love that!). Now the rest of the system needs to be as reliable as the model is capable.
Tools, browser, memory, state, retries, errors... There are so many ways an agent can fail even when the model knows exactly what to do.
Been working on some of that 👀
Mark Homan retweeted
41 years ago tonight, September 26, 1985, Woody Harrelson introduced the world to Woody Boyd on the fourth season premiere of NBC’s sitcom “Cheers”.
“Excuse me…My name is Woody Boyd…howdy, I’m a friend of Coach’s. Is he around?”
Mark Homan retweeted
One thing I have never, ever, never seen work:
-> Hiring an SVP Eng / CTO / Head of Engineering from an old, slow moving tech company
Usually they are really nice, and a good “people person”. At first, the team welcomes them.
And everything just slows down. So, so fast.
(And yes, same with head of any department, really).
Epic father-son moment ❤️❤️❤️
A SpaceX propulsion engineer brought his elderly father to watch a Falcon 9 launch at Cape Canaveral. His father had been a mechanic his entire life. He had never been to a rocket launch. He didn't understand orbital mechanics or payload deployment. He understood engines.
The engineer had worked on the Merlin engine for 4 years. The Merlin powers the Falcon 9. Every component his team designed was about to fire for 162 seconds and either deliver a satellite to orbit or explode.
The father stood in the viewing area and watched the countdown. When the engines ignited and the rocket lifted off the pad, the sound hit them 6 seconds later. The ground shook. The father grabbed his son's arm. Not from fear. From recognition. He knew engines. He had spent 45 years listening to them. This engine was different from anything he had heard in his life.
The father didn't speak for the entire ascent. When the first stage separated and the booster began its descent back to the landing pad, the father started crying. The mechanic who had spent 45 years under cars and trucks watched a rocket engine fire in reverse to land itself upright on a pad from the edge of space.
He turned to his son and said "you built that?"
The engineer said it was the single greatest moment of his career. Not the launch. Not the landing. The question. His father, a man who understood engines better than anyone he knew, looking at the most advanced engine ever built and asking his son if he built it.
Elon's vision of Mars is abstract to most people. But the moment a mechanic's son brought his father to watch the engine he built change the world is the moment the mission becomes human. It's not about Mars. It's about a father who finally understood what his son had been doing all those years.
Mark Homan retweeted
AI is a big W for 40-somethings. Old enough to have learned how to do things the right way, young enough to learn some new tricks.
Mark Homan retweeted
We are officially witnessing the biggest wave of infrastructure investment in modern US history.
Total investment in data centers and AI infrastructure is projected to average 3.63% of US GDP per year from 2025 to 2032, the highest proportion among major infrastructure buildouts since the 1800s.
The previous largest investment, railroad infrastructure, represented 2.24% of GDP per year in 1870-1890.
This was followed by highway investment that averaged 1.13% of GDP in 1956-1973, while telecommunications and fiber infrastructure averaged 1.10% in 1996-2003.
By comparison, electrification stood at just 0.50% of GDP in 1905-1925, while canal investment accounted for 0.66% in 1836-1841.
This comes as AI and data-center infrastructure investment is projected to total ~$10.3 trillion between 2025 and 2032.
The AI buildout is the largest infrastructure investment in modern US history.
Mark Homan retweeted
A CS undergrad asked me where he could have most effect in the AI age. I said probably at either extreme: either close to the technology, actually making LLMs, or close to the customer, using AI to give them exactly what they want. Or maybe both if you can stretch that far.
Mark Homan retweeted
BLACKSTONE JUST TOLD ITS INVESTORS THIS IS NOT THE DOT-COM BUBBLE.
Jon Gray runs the largest alternative asset manager on earth. He just showed the room the exact number that separates 2026 from 2000. And it is not close.
Blackstone deployed almost $100 billion into data centers this year alone.
Six gigawatts of new capacity. Their tenants will add another $200 billion in chips on top of that.
Blackstone did not do this because they were guessing.
"hyperscaler capex, five companies, $415 billion last year. that number has doubled this year to $820 billion. that's equal to 2.5% of the GDP of the United States"
"SK Hynix today trades at a four P/E multiple. it is not 2000 when Cisco was trading at 150 times earnings"
Then he showed the cost of building one AI factory:
"$55 billion for a gigawatt"
"the beef is the return on investment"
bookmark & watch the moments worth watching twice ↓
FUNDSTRAT JUST TOLD WALL STREET THE BEAR CASE IS BROKEN.
The strategist who called the 2023 rally when Wall Street was bearish just explained why this is not the top.
Tom Lee co-founded Fundstrat 12 years ago and is its head of research.
He has been publicly bullish through every scare in the last 12 years - inflation, rate hikes, tariffs, AI unwind, oil spike, government shutdown.
The S&P is 2.6% off all-time highs after all of it.
"this year earnings are up 25% and the market's only up 10. so the market got cheaper"
"demand to supply right now for chips is called 13 to 1"
"investors are underestimating earnings by probably 25 30% next few years"
Then he named the year we are actually in:
"this is a 1997 moment, not a 1999-2000 moment"
bookmark & watch the moments worth watching twice ↓
Mark Homan retweeted
It’s weird airlines don’t make it easier for you to jump on the earlier flight when it means you’re less of a liability and free up space for them to sell
Same with trains . If there is space. Get people out of the way
Mark Homan retweeted
I've been covering politics since 2008. The anti-AI-regulation takes from the left (by no means all/most of the left; Bernie disagrees!!!) might be the most literally incomprehensible political position I've ever encountered.
Mark Homan retweeted
There’s an African proverb that I love:
“If a tree does not know how to dance, the wind will teach it.”
Mark Homan retweeted
I think of this like testing. We all do deliberate pacing when it comes to pre-release R&D and testing. And having more outside/3P testing/testers is a good thing. And as the stakes get higher, one should take all the time they need! If not you will anyway lose permission to operate. That is how we operate everyday.
Mark Homan retweeted
Fact: 80% of the game is about subtraction, not addition.
Few understand this.
The best founders in the world like @elonmusk or @tobi “go ultra-hardcore on deletion and simplification.”
Luca Ferrari says Bending Spoons employs this idea of “Relentless Simplification” across their businesses:
“Humans have a tendency to add complexity and do things that destroy value.”
“If you leave an organization, almost any environment unattended, and you don't provide guidance in this regard, it will tend to become more complicated. People will add parts. It could be expanding a team or adding a step to a process, or adding an entire new process. If it's a product, adding a feature to the product. New rules. It applies to almost any human endeavor.”
“People tend to add pieces, they very rarely remove pieces.”
“If you don't make a conscious effort to achieve simplicity, and avoid this increasing value-destroying complexity, that's how we got to our modern society with all the bureaucracy and complicated regulation.”
“We have this principle whereby we ask everyone who works here, every time someone is suggesting that we should be adding complexity, the burden of proof is on those making that suggestion. The people who support the thesis that we shouldn't be adding complexity don't need to prove it. They just have to raise a flag and say, ‘I don't think we should.’ The burden of proof is on those who want to add complexity.”
“The other part of relentless simplification is that we want people to be on the lookout for existing complexity and suggest that we should remove it.”
Mark Homan retweeted
Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it's not worth pursuing.
We also need to accelerate and spread the benefits of AI, such that they are diffused broadly across countries, communities, and companies. This requires a frontier ecosystem in which both closed and open-source models can thrive.
And for firms, it’s imperative that they retain full control over their unique and tacit knowledge. Every organization should be able to build its own continuous learning loop/hill climbing machine, without becoming dependent on any one model provider, and have the ability to embed its own knowledge into models and weights they control.
So, in this context, we welcome the research, focus, and deliberate pacing needed to get alignment right as the design goal. We also welcome ideas like "embedded evaluators" and the broader efforts to develop the mechanisms to make this more than just talk.
The key is that this cannot be controlled by a handful of entities, but must have broad representation across the ecosystem, countries, and fields, including academia.
This is the approach we are taking: broad access and choice at every layer of the AI stack; enterprise control of learning loops and models; and the “Code of Conduct” that underlies our own first party MAI models that we’ll publish tomorrow for public consultation.
💯
Gen X defined:
Ages 45-61
Looks 35-40
Will 100% throw hands
Doesn't care about your feelings
Cusses a lot
Will make you cry with words
Great work ethic
Pragmatic
Zero tolerance for stupidity
Skeptical of authority
Doesn't trust anyone at 1st
Extremely loyal friend
Figures shit out
Most likely your boss
Works hard, plays hard
No fear
Sarcastic as fuck
Still listens to the same music
Knows lyrics to Rock, Rap & Country
Proficient in analog & digital tech
Self reliant
Adaptable to any environment
Just wants to be left alone
Mark Homan retweeted
Dario's essay points towards the right path forward. The details need working through, but the direction is correct for meeting this critical moment.
This is also why we recently put out our proposal for an industry-wide standards body for frontier AI. xitter.cf/demishassabis/status/2…
We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.
Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training.
You can read the full post here: darioamodei.com/post/we-must…
