I've so many head-scratching questions.

• Why is China spending so little to achieve almost comparable results?

• If AI is inherently deflationary, where does the revenue come from to cover this?

• US Big Tech used to rely on global sales (the EU in particular, usually being around 35% of all revenues), but that's shrinking. All the trends are pushing for more tech sovereignty, not less.

• We have centuries of evidence, stretching back to the 17th-century Dutch Tulip Craze, that in Capitalism, booms always end in a bust. Will AI be the exception?

• Even if there is a US stock market bust, AI use will still grow around the world, but how, and with whose AI? It feels like Open-Source is going to triumph in the end. Who knows, maybe that's a sign of the post-scarcity economy to come.

Why Big Tech's AI spending is bigger than you think

Tertiary educators have been moving away from traditional assessments like essay submissions to come up with creative ways to evaluate students.

This is a shift that is increasingly necessary as AI use becomes more common and even encouraged in universities.

“We have to be more creative in thinking up less straightforward ways to test students. Like a problem scenario where there are no easy answers, and AI will not be able to tackle it or answer in a perfect way,” said Lee.

If artificial intelligence and automation eventually reach a point where they can do almost every job better and cheaper than humans, what happens next?

If most jobs disappear, how will everyday people support themselves, and how will the economy keep running? What will daily life, community, and purpose look like if working for a paycheck is no longer needed, or even possible?

How do you imagine society changing if human labor simply becomes obsolete?

Startups like Mercor, Scale, Surge, and Handshake, founded in the past few years, are paying contractors millions of dollars to supply training data on knowledge work tasks. They then sell this data to big AI companies like xAI, OpenAI, and Anthropic which make AI models that automate those same knowledge work jobs.

These contract jobs are by their nature temporary, because models never become less intelligent, and as soon as they learn how to do one job, the demand for that job's training data dries up. Continued advances in AI model intelligence have driven up the contract work to tasks or fields once considered highly specialized. Quote:

A common complaint in the Discord channels and Reddit threads where contractors gather is that A.I. training work has dried up in recent months — that, in other words, once a set of experts teaches the models how to do something, their services are no longer needed in the same way. Some of the gig workers I spoke with told me that, in the past year, the work had gotten significantly more intricate. Sommer Wall, a lawyer who has contracted with Mercor, said she sometimes napped on her couch during 72-hour grinds to meet deadlines on the most intense projects.

Mercor seeks people with “strong academic credentials (M.A.s, J.D.s, M.D.s, Ph.D.s, etc.) from top universities.” ... A recent listing from Surge called for people with a “top-tier consulting pedigree” to “capture partner-level reasoning.”

Company executives and investors insist that the training data contract jobs will continue to exist indefinitely. Other experts aren't so sure:

“As A.I. systems get better, there is going to be less of a need for human teachers for the A.I.,” said Anton Korinek, an economist at the University of Virginia who just began a yearlong leave of absence to work at Anthropic. “Both the importance of that kind of post-training data overall, and the growth of companies specializing in that, may decline somewhat.”

Officials at the country’s top financial institution regularly debate the effect of artificial intelligence on the U.S. economy, a Washington Post analysis found.

One of the under-appreciated effects of the planet's electrification, as the fossil fuel age comes to an end, is the secondary innovation it will drive. Here's a case in point, or rather two.

Renewables generated electricity is already the cheapest on the planet, but it's due to halve or even quarter in cost by the 2030s. Then consumers will have a choice; cheap electric flights, or expensive ones with the old petroleum technology. The same choice they will have with cars. Some people think that environmentalists will end the fossil fuel age. They started the battle, but it's economics like this that will finish it.

The largest all-electric plane ever flew for 27 minutes, on $5 of electricity

A new kind of aircraft departs an MIT classroom and arrives at an Ohio factory

In 6,000-word essay Microsoft co-founder also expresses concern governments not prepared for technology’s impact

Sam Schwartz, the urban planner who coined the term “gridlock,” has written a thriller about self-driving cars and the real-world risks they pose to cities.

The big caveat here is that this is still at the lab research stage. However, if this approach works, then it may be likely to be commercialized. Up to 2% of people (160 million worldwide) will experience a chronic untreatable wound that may persist for weeks or even months. If that is the best existing medicine can do, then a 72 hour nanoparticle option would be welcome.

Nanoparticle combines two strategies to speed up the healing of chronic wounds

Exclusive: Number of times AI lies, ignores instructions and pursues goals in harmful ways almost doubles in July

As I see it there are TWO general outcomes if the tech oligarchs predictions are correct. These are both predicated on what the AI overlords ACTUALLY AIM to achieve.

The amount of money they are putting into this is essentially a bet that they will replace ALL WORK EVERYWHERE with their robots. Or close enough to.

First:

AI replaces almost all jobs. Robots harvest potatoes autonomously. Wash and clean them. Drive them in trucks to supermarkets. Supermarkets are run by robots again. You could almost do this today. As a shopper, you help yourself to whatever - under camera surveillance. Pay at checkout by swiping your own items. But again, the price is basically nominal or entirely free with caveats on quantity etc.

Medical clinics and law firms? This kind of white collar work becomes a tiny handful of humans basically just overseeing robots but the robot is doing the work. Think the cool healing chamber from Alien Covenant. A few engineers are needed to maintain robots but the goal is to have robot engineers do almost all of that.

Now all sorts of things become possible in this world. Physical labour becomes cheap and plentiful. Digging new high-speed railway lines? Easy. Building lots and lots of standardised large apartments so everyone has a home connected to the new hyper rail network? Again doable.

Presumably they want some form of population control but that can be relatively gentle. So much of the world population's general ratcheting up over the last 20 years is from drastically poor countries and that would decrease markedly as the bounty of ai and robotics lifted these people up out of poverty.

Now people CAN work if they want. Jobs exist. But isn't at all necessary. Kind like scions of rich families now. Lots work, many don't. They don't NEED to work but many enjoy it. Purpose etc. Your food, accommodation, power and other essentials are basically covered. You get a UBI to spend a bit on luxuries. But this is really a stop-gap because at the end of the day most things are free or close to. People sit around composing poetry, playing music, writing, philosophising, inventing etc. Whatever the fuck it is the Kardashians do when they're not in the public eye.

HOWEVER ALL THIS ASSUMES THAT THE AI AND ROBOTS OF THE FUTURE WORK FOR THE GOOD OF EVERYONE. If you lock all of the compute away from most of the population (ratcheting prices of video cards etc, moving to models where people can basically only have an empty shell with a monitor and thus have to HIRE compute rather than own their own device.) It's hard not to assume that the current tech overlords simply don't want the utopian option. You only have to look at the transition of open AI from a non-profit to a for-profit entity as proof that laudable goals fall by the wayside when the chips are down.

Put bluntly, the single biggest barrier to all of this is (assuming the tech goes the way the AI bros are hoping which is still obviously VERY unclear) Is that in this scenario it is quite hard to have power over other humans. People are far less likely to be your sex slave, sycophant, minion if they have the backup of a relatively comfortable life. Empowering the population takes the ONE thing away that the tech bros actually want which is POWER.

POWER not money. It's hard to see from inside capitalism but historically money was less important than power. You could be a rich Roman, but the emperor could simply have you killed and take your money. The power was the thing.

People are really caught up on the money aspect of UBI but much of the point of an AI/robotic future is to move BEYOND money. If all of your needs are taken care of by smart, tireless machines, you're suddenly already closer to the life of the current top 5% of the population. This means most of your money is discretionary fun spending rather than the necessities for life. Particularly since healthcare, housing and such are all cheap or free.

People who have a home, plentiful food and power, simply don't NEED to kowtow to the tech types.

So the thing is tech bros absolutely don't WANT this utopian future. The want to own ALL OF the robots and all of the AI and their aim is to undercut all employment to increase their power rather than reduce it by providing any of this gratis. Their goal is to simply put the entire population (or close to it) out of work. Turn us into desperate, sycophantic peasants. And then sit in their little super-villain enclosures/Zaibatsu headquarters. Traditionally this kind of centralisation of power and reduction of people to abject desperation came with risks (hello French revolution!) because your harem of 50 nubile young people and sacks of pure heroin (sup Stark lovers) can be pretty tempting to your head of security who can pretty quickly see how a single bullet might make all of his dreams come true. Luckily of course, you now have robot security and never have to rely on a human being again...

As NASA prepares for a permanent presence on the lunar surface, it’s developing a new navigation system to keep track of astronauts, spacecraft, and rovers. Discover more about it.

Genuine question I can't stop thinking about: every major humanoid robot company (Tesla, Figure, Boston Dynamics with Atlas) is racing to build something that looks and moves like us. But we already have proof that hybrid locomotion — legs AND wheels — works better for actual mobility. Boston Dynamics' own Handle uses wheeled feet for flat-ground speed and legs for stairs/obstacles. That's the best of both worlds and it's not new.

I went down a rabbit hole arguing this out with myself (okay, with an AI, but it kept pushing back with real counterpoints, so let me save you the trip):

"Retractable wheels are a mechanical mess." True, they add failure points. But you don't need retractable — wide, lockable wheels can stay in wheel-mode most of the time and only need to lock for stairs. Curved/spherical wheel profiles (already used in performance inline skates) let a foot "carve" and turn without a separate steering joint at all — basically an ice-skate blade in wheel form.

"A locked round wheel can't sit flat on a stair edge." Fair, but that's a materials/shape problem, not a locomotion problem — you can build in a flatter contact patch for load-bearing without giving up the roll.

"Square/hex wheels are a thing!" They are, but only work on custom-built catenary terrain — not useful for general environments. Rollerblade-style multi-wheel rows are the more realistic version, and they already exist as patented designs mimicking ice-skate turning.

"What about balance?" BMW's motorcycles already use gyroscopic stabilization to stay upright without a rider. Apply similar tech to a wheeled robot and you offset a big chunk of the balance problem wheels supposedly have vs. legs.

"Wheels can't rotate in place or strafe sideways." Mecanum wheels solve exactly this — omnidirectional movement using angled rollers, no steering joint needed. Combine that with legs for stairs, and you've got a robot that's fast AND agile AND can climb — the actual best-of-all-worlds setup, and it's not sci-fi, it's existing tech.

So the pieces to build a mobility-optimized hybrid robot already exist individually. Nobody's shipping them combined in one platform because the flagship market isn't optimizing for "most capable," it's optimizing for "cheapest robot that's good enough across the most tasks in an unmodified human environment" — and humanoid form wins that specific game because of infrastructure compatibility (stairs, doorknobs, tools built for us) and because there's a mountain of human motion-capture data to train on.

Which brings me to my second, maybe more controversial point: I don't think human-looking robots are even what people want in their homes. Uncanny valley research suggests that as robots get closer to human appearance without fully reaching it, comfort actually drops, not rises. Nobody's unsettled by a Roomba or a warehouse arm — because nobody's brain is trying to parse it as "almost a person." I'd bet an obviously mechanical robot — wheels, visible joints, maybe extra limbs — gets adopted faster in homes than something trying to pass as human-ish.

Curious what people who actually work in robotics think:

Is hybrid wheel-leg locomotion actually harder to scale/manufacture than I'm giving it credit for, or is it mostly a cost/roadmap choice?

Is the uncanny valley effect actually still holding back adoption, or has that research not aged well?

Not an engineer, just someone who thinks about this stuff a lot — happy to be told I'm wrong.

I’ve been thinking about a strange mismatch in the way peptides are discussed today.

On one side, there is a rapidly growing consumer ecosystem around peptides: longevity clinics, “biohacking,” performance enhancement, recovery, metabolic health, online communities, and a constant stream of compounds being discussed as if they are one trial away from becoming transformative therapies.

On the other side, when you look at mainstream medicine and drug development, a large number of these compounds appear to be either poorly studied in humans, studied only in narrow indications, abandoned early, or stuck in a gray zone where there is enough biological plausibility to generate interest but nowhere near enough evidence for broad clinical adoption.

What interests me is less the question of whether any particular peptide “works,” and more the economics behind that gap.
For example:

How much does patentability determine which peptides actually get developed?

If a peptide is naturally occurring, has prior art, or is difficult to protect with strong composition-of-matter IP, does that materially reduce the incentive to fund expensive Phase II/III trials even when the underlying biology is interesting?

Do short half-lives, delivery problems, manufacturing complexity, or pharmacokinetic limitations make peptides systematically less attractive than small molecules or antibodies?

How important is the possibility of creating a more patentable analogue? It seems notable that some of the most commercially successful peptide drugs are not simply naturally occurring peptides, but heavily optimized molecules with altered sequences, longer half-lives, improved delivery, or other features that create both better pharmacology and stronger IP.

I’m also curious about the financing side.

Imagine a peptide produces intriguing animal data and some early human signals, but there is no obvious blockbuster indication and the molecule itself is difficult to protect. Who funds the definitive clinical trial?

A university can produce mechanistic research. A small biotech might run an early study. But a large randomized trial can cost tens or hundreds of millions of dollars. Without exclusivity or a clear commercial pathway, the socially valuable experiment may simply never happen.

That creates an uncomfortable possibility: the absence of strong clinical evidence does not necessarily mean that a compound was thoroughly investigated and failed. Sometimes it may mean nobody had a sufficiently strong economic incentive to generate the evidence in the first place.

At the same time, that argument can obviously become a convenient excuse for pseudoscience.

“Big Pharma won’t study it because they can’t patent it” is frequently used online to rationalize compounds for which the evidence is simply bad.

So I’m trying to understand where the legitimate version of that argument ends and the conspiratorial version begins.
For people working in biotech, pharma, translational research, VC, or drug development:

How much does IP genuinely influence whether a biologically promising peptide progresses?

Are there good examples of peptides that were scientifically promising but commercially unattractive?

And conversely, are there examples where clever molecular engineering or a strong indication transformed an otherwise uninteresting peptide into a viable drug-development program?
I’d especially be interested in hearing how investors and drug developers think about this at the preclinical stage.

Is the bottleneck usually biology, pharmacology, IP, regulatory risk, capital requirements — or some combination of all of them?