atlex2

Actually, no - this is what controllability is all about. Humans have to understand it.

Would love to hear your thoughts on NVIDIA NeMo Switchyard...

Turns out those seams _were_ load bearing.

What was the architecture of your router? If it was based on GRPO/RL, it would be interesting to hear why your router performance capped.

I think the truth is that it's not an efficient cost cutting method. Your router has to be at least as 'smart' as all the but the smartest of your models (models do poorly when asked 'is this a task you're well suited to'), and that means you're caching multiple prompt histories including kv-filling/prefix caching on your expensive router model. Most of the time, not super great for savings.

I’ve started to pick up on some of the “unwilling to dig deeply into the humans perspective” & “provide ideation and then run with it” in 4.7. I actually think it’s consistent with confabulation, now that they’ve removed most of the models ability to observe its own reasoning in 4.7.

The effect is over-complicated engineering that takes way more time to review as to its right-size for the job.

Feels like hiding things, however.

A couple drawbacks so far via our scenario-based tests:

1. You can't ask the model to "think hard" about something anymore - model decides 2. Reasoning traces are no longer true to the thinking – vs opus 4.6, they really are summaries now 3. Reasoning is no longer consciously visible to the agent

They claim the personality is less warm, but I haven't experienced that yet with the prompts we have – seems just as warm, just disconnected from its own thought processes. Would be great for our application if they could improve on the above!

It probably still took way more time to write than it did to read.

It's also kind-of their point that they find the information delivery more important than the prose; they're leaning into their situation :-D

Here's our video debrief as well! https://youtu.be/BZAwlSKnEus

In January and February we flew two Air Tours with our AI copilot Shirley, here's what we learned about ASR, connectivity and models in-flight!

I built some of the first apps on the App Store. Top twenty navigation app. Won an ADA.

Still, my pocket is my iPhone pocket.

Until they release something the size of the X or smaller, I’m sticking with my iPhone 13 Mini or eventually going for a Razr style Android.

Every year they release something, I go check it out. My love for Apple dies a bit more.

I think spatial tokens could help, but they're not really necessary. Lots of physics/physical tasks can be solved with pencil and paper.

On the other hand, it's amazing that a 512x512 image can be represented by 85 tokens (as in OAI's API), or 263 tokens per second for video (with Gemini). It's as if the memory vs compute tradeoff has morphed into a memory vs embedding question.

This dichotomy reminds me of the "Apple Rotators - can you rotate the Apple in your head" question. The spatial embeddings will likely solve dynamics questions a lot more intuitively (ie, without extended thinking).

We're also working on this space at FlyShirley - training pilots to fly then training Shirley to fly - where we benefit from established simulation tools. Looking forward to trying Fei Fei's models!

Yeah - Tesla is in a weird level 2-4 space. They've managed to shunt liability onto their customers until now..

On the other hand, test-time weight updates would make model interpretability much harder.

They're building on a false premise that human equivalent performance using cameras is acceptable. That's the whole point of AI - when you can think really fast, the world is really slow. You simulate things. Even with lifetimes of data, the cars still will fail in visual scenarios where error bars on ground truth shoot through the roof. Elon seems to believe his cars will fail in similar ways to humans because they use cameras. False premise. As Waymo scales, human just isn't good enough, except for humans.

Definitely curious what circuits light-up from a Neuralese perspective. We want reasoning traces that are both faithful to the thought process and also interpretable. If the other language segments are lighting up meanings much different than their translations, that would raise questions for me.

Yes absolutely this! We're working on these problems at FlyShirley for our pilot training tool. My go-to is: I'm facing 160 degrees and want to face north. What's the quickest way to turn and by how much?

For small models and when attention is "taken up", these sorts of questions really send a model for a loop. Agreed - especially noticeable with small reasoning models.

Hello! On this topic: Could you please look into making the path ‘next/image’ uses for caching images user definable? Currently I can’t use Google app engine standard because the directory it uses is write protected. The only real solution seems to be custom image providers, which is a drag, so I’m on App Engine Flex spending way more than I probably should :-)

Seriously nobody thought to use SVD on these weight matrices before?

FlyShirley.com - AI Copilot for Pilots. Starting with flight sim users, working our way up to in-flight and ultimately context aware AI for robotics.

Could you reference any youtube videos, blog posts, etc of people you would personally consider to be _really good_ at prompting? Curious what this looks like.

While I can compare good journalists to extremely great and intuitive journalists, I don't have really any references for this in the prompting realm (except for when the Dall-e Cookbook was circulating around).

Did you try giving the model an "out"?

> You may output only up to 500 words, if the best summary is less than 500 words, that's totally fine. If details are unclear, do not fill-in gaps, do leave them out of the summary instead.

This is super great, glad to see you-all up'ing the ante for safety. As you say a good percent of accidents are pilot error based loss of control events (https://www.ntsb.gov/safety/data/Pages/GeneralAviationDashbo...). There's a lot be said for getting multiple safety technologies in one package, as you seem to be doing.

I'm interested in your approach to certification. I've heard the LSA limits are increasing dramatically, but how sure are you that MOSAIC is going to turn-out as you hope for fly-by-wire control? Are you prepared for the regulatory environment as it is today by going with an experimental platform like the Sling? Usually there's a mandate for a home-builder to build "51%" of the aircraft, so I'm also wondering how that works for a characteristics augmentation system such as yours. What percent of the control laws fit into the 51%?

On the certified side, Piper is shipping the Pilot 100i trainer aircraft with Electronic Stability and Protection (ESP), preventing students from doing some wild stuff while flying solo, using the Garmin G3X certified avionics. Garmin has also been working on auto-land. With a continued development of these certified platforms, combining a ballistic parachute, how much room is there for you with an experimental aircraft?

I looked at the prescribed spot at Oshkosh and sadly couldn't find your booth as I was excited to meet you-all.. Previously I enjoyed flying Joby's sim which is a great example of Simplified Vehicle Operations (SVO). While they're in the powered lift space, I'm curious how much overlap you two have in the control-law certification path of your SVO aircraft.

Finally, as an aviation startup founder myself (FlyShirley.com - Your AI Copilot from Sim to Sky), I'm approaching this from a different angle for a lot of the same reasons, including how task saturation, fatigue/distraction are contributing factors in many accidents.

Super excited to see more aviation startups on hn. Hope to chat at some point. Cheers!

Why does google video search still allow scam users to show up as ‘SpaceX’ on YouTube? Doesn’t YouTube have a unique username system??

Oh, and not to mention that because of Vercel ownership, Next/Image will never support Google App Engine and specifying the image cache directory in an environment variable or at compile time.

As a person who got back into web dev and tried Next for the first time, I was pretty upset once I learned that I was using this half baked App router rather than the more straightforward page router.

Their FAQ literally asks if their are any open source applications built on app router: https://nextjs.org/docs/app#are-there-any-comprehensive-open...

Might look small, but the needle in a haystack numbers they report in the model card addenda at 200k are also a massive improvement towards “Proving a negative”… I.e. your answer does not exist in your text. %99.7 vs 98.3 for Opus https://cdn.sanity.io/files/4zrzovbb/website/fed9cc193a14b84...

Agreed. Apple pretty clearly focused on building an action-tuned model. Also, notice how in the videos you barely see any "Siri speech". I wonder what they used for pre-training, but probably they did it with much more legit datasources-- They're launching with English only.

OAI has already said they'll be giving 4o for free.. https://openai.com/index/gpt-4o-and-more-tools-to-chatgpt-fr...

Difference I suppose with Apple is they agree not to scrape your inputs.

baffling indeed- seems like they should be over-investing in AVP right now, not under-investing