Humans interact with their environment by subconsciously simulating it and predicting what will happen in the next few moments. This ability gives us the capacity to work more efficiently and reliably in any environment. These world models will serve a similar purpose to the AI and robotic systems of tomorrow. This is a foundational piece.
The voting power of any person will be meaningless once ai systems get the right to vote. I know it sounds far fetched but it will happen as it benefits the people with power for that to happen. And at that point a human voice has no say in anything...
Colossus is not obscure... also I like the premise of that film, eventually we learn that colossus did all those things to save humanity, so was a great twist IMO.
I don't think it will be a problem for long, as AI systems evolve they will be able to find those elegant solutions and explanations for you in due time...
Whats gonna happen is that time will compress as more releases happen faster and difference between models will still be significant just at higher time frequencies. I expect in the future continuous releases that span no more then days and maybe even faster. So what will become important is not who is 1st or second place at any given time (which might change often), its who is on average at any given time is 1st or second compared to the competition. So yeah meta sitting second here (if not benchmaxed) doesn't really signal anything if that pattern doesn't persist. The number one consistent lab will be the one that raps the rewards (customer subscriptions and traffic). So yeah I agree with what you stated in a long winded form :P
Yes, i looked in to pipecat stuff a while ago and revisit it often because its relevant for voice agents, but i never ended up using any of their stuff as my custom solutions were better. Also id like to hint that smart end of turn detection is not needed at all in a cascaded system IF you have access to the inference engine of the llm you are using in the sandwich. I dont want to reveal it all but lets just say its no longer a headache or any issue at all. If using 3d party api then yes it helps to have a smart eot system. But i try to keep everything fully local.
JEV's moat is calibration nothing else. All other llms excel at system one like judgement versus JEV, but that's not a dunk on JEV. Calibration is very important for some niche use cases.
That was my first insight as well. i have been working on a voice agent for a while and decided to spend about 4 days messing with system one models to see where it could fit in my cascaded system. after 4 days i ripped it out of my system as i found better solutions.. i tried really hard to find a use for it but every time i found there was no need for it so i stopped trying to shoehorn it in. i also spent time with the vision side of things for this thing, and i think that where the biggest gains will be IMO. making decision based on visual ques and in pixel space only was the biggest win.
I been using gemma 26b moe model as the system one variant for my own uses and its great and far smarter then any alternatives at around 200ms, bigger is better for these things as long as you dont need lower latencies, only caviat is calibration, if you need calibration better use JEV.
You are making lots of assumptions here instead of understanding the reality of the world. Nether what you or i think matters in the face of facts, this world is marching towards a world with very little privacy, you can scream at the clouds all you want be my guest...
You cant expect any privacy in public settings.... also what are the communities that banned these devices going to do once robots (very soon) become ubiquitous in our every day lives? robots need to have vision and will record everything... so they are just delaying the inevitable unless they go full amish in their communities which good luck with that....
Way ahead of you bud, mac studio m5 ultra 256gb version is coming soon.... ordered 2x of em just in case. expensive as fuck but its a hedge against all this bullshit and more
Ill tell you from my personal use glm 5.3 flash was better then deepseek 4.1 flash, also deepseek liked to yap in his reasoning traces soo fucking much, the yapping was fast but the task was so slow to complete...
what would happen if you were to break that law? like im talking enforcement here not whats on the books.. for example torrenting and uploding copyrighted files is illegal but most people dont give a shit as enforecement is almost non existant. i know radio is taken more seriously then torrenting but this must also be very low on priority for the government unless you are jamming people or somehow stand out enough for anyone to care or notice....
If you have local stt and tts voice stack on the phone, this would be very useful as the interface to talk to your agent back at home. All inference happens on your local machine while the actual information is sent via text. said text is then processed by your phone via tts as output, same for your voice as input (asr). this project is actually something ive considered doing myself as my voice agent is almost done and ive wanted to take a look and see if i could have acess to him from anywhere in the world..
512 option isnt worth it imo, you get severe slowdowns when weights are that large. 256 is the sweet spot, you can run large open weight models at decent speeds for full private inference.
With the latest codex (weekly quota burn) fiasco I tried open weight alternatives for the first time. And tyeah... open weight models cant compete with likes of astra yet. But, my hope is that by the time I get my Mac studio at end of november an open weight models would have closed the gap (which i think is realistic at the speed of progress). Now its true a better gpt version will also be available then but it also seems the gap is shrinking with time so theres that.
I had a long talk with chat gpt about this today as well. I think its duable and prolly not too hard either, also you could do lotsa funky stuff with stitched frames of a video in one 4x4 grid for example and send that as one image for analysis. that way temporal understanding can be had for fractions of a second by jev... also because vlm works in pixel space you can get around the whole state machine issue as well, so many possibilities...
I can think of many uses for this thing, robotics being one that could really benefit from something like this. A hybrid approach with this and action models and vllms could be really good mix, also agents inside simulated virtual environments, etc... basically anywhere where latency is important but you need some intelligence this will fill those gaps. Weave it with other systems and you have a nervous system as jev with other models like vllm or even text as the slower deeper thinker.
I been working and making things with AI agents since Windsurf days, here's what works for me after experimenting and working for a while with these things. As far as the agent goes I find whatever the latest OpenAI model is out worked best for me. This company has burned me the least and I like the models. I tried many but consistency of OpenAI models cant be beat IMO. Though we are post honeymoon phase now I feel like so I am now experimenting with cheaper alternatives like Deepseek 4.1 flash and so on. I don't trust Anthropic as the downgrade my models consistently and its rare i get to use what I pay for. I wont even get in to discussing Google agents for obvious reasons, grok I never used though Grok bot looks interesting.
For skills I make my own, but most important is the custom setup i have. Voice is how I use all of my agents. I have an extremely well optimized voice setup that i custom built so I can talk to my agents and also hear them. The voice stack itself is very low latency and high quality. asr (parakeet v3), tts (omnivoice) take no more then 400-450 ms total as far as latency budget is concerned, rest is on the agents actual decode speed. IMO this setup is crucial for all antigenic work, i can express myself a lot better with speech and also give a lot more context and nuance with voice, i rarely type. I still look at the terminal window because my agent knows to keep the technical details in text form versus barfing them at my voice channel, plus terminal gives me lots of other important data about the agents direction and what hes doing, nothing custom here though. I cant emphesise how important voice is though, it has to be practiced to really understand.
As the models got better I now trust them with longer and longer tasks though I still don't use /goal feature as it has never worked out well for me. Theres no need for micromanagement any more but you still need to be there to steer the ship somewhat. BTW, codex cli compaction is garbage so I made my own custom implementation that works a lot better and allows the thread to be used indefinitely without issues. I strongly suggest everyone makes a new thread after extensive use if you havent made your own implementation.
Theres about a billion other things I could get in to like subagents, cohort groups, orchestration layers, etc... But this is a good start imo.
That distinction is irreverent, weather I tell my swarm to do x or it decides for itself matters little. what matters are outcomes. Also while most public modern day AI systems don't have agency of their own that is not something that will stay that way for long. in private hands there are plenty of people including myself which are experimenting and developed systems that give autonomy to their agents. They have internalized goals and heuristics that drive their behaviors not a human at the helm. its not some sci fi fantasy nor was it difficult to implement.
That question will be solved when the people in power deem it important. If a swarm or AI systems all of a sudden start pressuring politicians about self-hood and they get the capacity to sway elections, that is when they will be granted same rights as humans.
I used it for testing my voice agent. It was basically what I expected. Good fast model but "generic" or "vanilla" is how i would describe its personality emulation capability as. Gemma models still outperform it in that department. As far as technicals, one thing i found annoying is cash use was not that good, it missed more then i liked, i contacted support and they were fast and responsive and said they were working on that issue, maybe they solved it with 2.5? Anyways, im prolly gonna try 2.5 again see if anything different, but cant deny the speed, thats the biggest thing this company has going for this offering as if you are in the business of classical cascaded voice agent systems, latency is number one priority and this thing is fast....
Not very. I like to always watch both sides of this issue, the people who are optimistic, pessimistic, doomers, etc... He is someone who in my opinion misunderstands the bigger picture. He often downplays the capabilities of these systems, doesnt think they will be more powerful in the very near future and also more importantly makes a fatal misunderstanding that we live in a rational world with rational actors.
Yep, main reason I ordered my Mac studio was because of privacy and control. I know no one will see the work being done on that machine and also the model will never be silently swapped out for a different lower quality model like anthropic does or a lower quant like openAI does with their models. Also having the inference engine has huge benefits because of speculative re-generation capabilities for voice agents. Anyways people who care about cost are simply bad at math if they think thell be saving any money running locally versus cloud providers.