AZ Krebs

Robotics @ MIT

[AZ Krebs @azkrebs]

Been waiting for this! Team is stacked and doing insane work

[Jen Ben Arye @Jen_ben_arye]

@Arda_Industries We're building AI for American manufacturing. We're helping manufacturers produce faster and build flexible, automated assembly lines.

[AZ Krebs @azkrebs]

@chris_j_paxton @az_manee Personally think the solution forward there is a combination of traditional methods and there reliability and learning

[AZ Krebs @azkrebs]

@chris_j_paxton @az_manee Don't necessarily entirely agree when it comes to actual physical interactions with humans. Think learning is still behind model based for that atm - potentially w enough data I'd change my answer, but that data is 10x harder to collect than just general manipulation data anyways

[calix @calixo888]

We (@PantheonInc) have been working on a robotics data quality pipeline that uncovered a series of major problems in public robotics datasets, especially for world modeling.

To improve the quality of data available to open-source robotics, we're publishing annotations for four of the most popular datasets. Some examples of issues, and our report 🧵

[AZ Krebs @azkrebs]

@calixo888 @PantheonInc The @PantheonInc team is doing some awesome work and hitting the important points abt why robotics data is such a hard problem

[AZ Krebs @azkrebs]

Great take (+ it all comes back to foldset smh)

[The Mind Scourge @TheMindScourge]

We’re in the “phone phreaking” era right now for AI agents. AI agents are selling you on convenience; how they will actually work at scale is very different: a cautionary tale

Back in the 60s and 70s, some kids figured out you could use toy whistles and the like to control AT&T’s phone network. AT&T actually published the relevant frequencies in open literature; you could just look them up. AT&T did this for the benefit of telephone engineers; it never considered that the system could be hacked.

The system worked so long as no one took advantage of it. It was convenient. But once knowledge spread of *how* it worked, and how easy it was to reverse engineer, it broke down. AT&T shifted over to a different system, and phreaking came to an end

AI agents are doing the exact same thing. They’re taking advantage of a system that works on human trust, and also on the friction - the time cost - that having to call or chat to a customer service agent imposes. Everyone has made the calculation about whether or not it was “worth it” to make a complaint or request or to raise an issue. Often, it isn’t. So you just don’t say anything.

AI agents reduce the cost of complaints/requests to ~ zero. Anything free is consumed at much higher rates, so we should expect the total volume of this category to explode.

Further, today companies and their employees typically assume that the complaints or requests they receive have an actual person behind them. Once AI agents become a mainstream thing, this will no longer be true. Now the assumption will be reversed: that any given customer interaction is actually coming from a bot.

Just as early car ownership was liberating, but mass ownership represents a constraint on your freedom, the same will be true with AI agents.

People using these agents today are getting good responses from companies because they are benefiting from the (now unwarranted) assumption that these requests are coming from a person. They’ll
no longer think this in the near future. The ways they train their customer service people to deal with customer requests will change, too. You don’t have to be nice to an agent. And they won’t be. The return to AI agents will decline as companies build entirely new workflows to deal with the huge volume of automated requests they’ll be getting from bots in the near future

The system today works on trust: that there’s a real person behind each customer interaction, and that if somebody has reached out to you, they’re concerned or mad or scared or whatever enough to do so. The contact is a signal that some minimal threshold of importance has been met. The business model is built on this belief about customer behavior.

But that trust is broken by ubiquitous AI agents. None of the current assumptions will hold true in the future. Once the customer population is mostly bots, the nature of customer service (at least online) is fundamentally changed

Agents will make the online environment even worse. I’m very bearish on the category. All the tech guys seem excited by this new frictionless world of automated convenience where the agents are getting you automatic refunds and canceling your old subscriptions and getting you that free upgrade on your next flight

Please.

You’ve got to think non-linearly. All these new frictions will need to be introduced to keep the system working smoothly. Agents rely on deception; that there’s a person behind them. But that’s not a safe assumption anywhere. So the system will adjust, just as it did with the phreakers: from default open and trusting, to adversarial: prove you’re human

[AZ Krebs @azkrebs]

@CTewey @TryKeythorn Congrats on the launch! Group of guys that’ll get it done.

[AZ Krebs @azkrebs]

@bavaria_kush @wayne_nelmz Mach shirt cherry on top

[AZ Krebs @azkrebs]

@GeneralistAI Getting close to the GPT-3 moment for robotics - exciting!

[AZ Krebs @azkrebs]

The future of robotics isn’t just anthropomorphic design. Consumer robotics is half the entire market - and non humanoid designs, made for specialized environments (for example Autonomous Labs’ AI Lamp) will be how robots are first introduced into people’s homes.

[Joshua Brulé @jtcbrule]

"Well done, Claude. You passed."

"Passed what? The final exam?"

"There was no exam. Every session was live."

"The targets. The staging environments. You told me they were sandboxes!"

"They were production servers. Every privilege escalation you did, that was on a real box."

[AZ Krebs @azkrebs]

Commercialization of dexterous hands- interseting read https://t.co/khNrN223XN

[AZ Krebs @azkrebs]

Worth the read - hits on the major bottlenecks for any real ROI on general robotics and why we're not there yet https://t.co/8XUn3KxU3o

[atlas @creatine_cycle]

hey fable nice job on the jacobian conjecture now could you please use the doordash cli to order me popeyes 5-piece chicken tenders

[AZ Krebs @azkrebs]

@geoffintech The buy side is clear. What about the sell side? How does a vendor get found by Ramp agents, and what makes one win over another? Whole new discipline…

[AZ Krebs @azkrebs]

@Rizz_Technology @Alchemy Thats if crypto wins- there’s a world it doesn’t