Algorithmic thinking has nothing to do with writing code. It has to do with systematic thinking. Playing puzzles or games like chess and go trains you to plan ahead. Thats what algorithmic thinking is all about.
One other thing that might get over soon is "Slack", I think in a year or two the enterprise might not need slack anymore. It served its utility at some time its will not be required in future. Discord on the other hand is powering communities so that might empower agents. Which means email is going to comeback for rare personal communication.
There is absolutely no need for this to exist in physical form. It is perfectly alright to run this on a simulation in Logisim Optimize as long as you desire and then once that is done, implementing it in physical form is just a matter of assembling it, which mostly can be done by many print pcb and solder on demand services.
Looks like a Tiny Analytic transformer, RNN is arguably a better choice if you are gonna handwire an architecture to mechanically do addition. Learning is about discovering the patterns and algorithm from data. Wiring a machine to follow a procedure defeats that purpose.
I understand that what Taalas is claiming. I was trying to actually describe that model on a hardware is some not something new Or unthought of The natural progression of FPGA is ASIC. Taalas process is more expensive And not really worth it because once you burn a model on the silicon, the silicon can only serve that model. speed improvement alone is not enough for the cost you will incur in the long run. GPU's are still general purpose, FPGA's are atleast reusable but wont have the same speed. But this alone cannot be a long term business. Turning a model to hardware in two months is too long. Models already take quite a long time to train. Anyone going down this strategy would leave wide open field to their competitors. Deployment planning of existing models already so complicated.
For a real world use case, you would need an FPGA with terabytes of RAM. Perhaps it'll be a Off chip HBM. But for s large models, even that won't be enough. Then you would need to figure out NV-link like interconnect for these FPGAs. And we are back to square one.
Boston dynamics is far behind plus the robots are so cheap , even their dog is cheaper than BD. I dont think their humanoid can even catch up to this price. I am sure US Army and for the chinese counterpart Chinese army will be their biggest customers. But i wonder how will this workout in situations like Plane hijack, fire fighting and other such places where human lives cant be risked to save more human lives. (Please Dont downvote because your american patriotism is poked try replying.)
No, it’s actually the math of overwriting. Imagine you hiked down into a valley Task A and settled there. Then, you decide to climb a new mountain to find a different valley Task B. You successfully move to the new valley, but in doing so, you destroy the path back to the first one. You are now stuck in the new valley and have completely 'forgotten' how to get back to the first one.
People will only build it by hand if there is a market for it. Otherwise it'll be mostly hobby software build for learning and entertainment (opensource). Businesses don't mind factory software Although the cost of developing software is going down and will be almost free, in that case, the price is actually of taste. The best designed easy to use Interface. My guess is there will be some people, even in future, who would prefer custom handmade artisanal software written entirely by hand. Those will be probably artisanal software collectors. Maybe there will be some art galleries in future who will auction this software as art pieces to be demonstrated in museums or galleries. These will be rare events. Most commercial software will be factory made.
Could be but the central bulb as made on the coins is unlike a fennel https://en.wikipedia.org/wiki/Silphium , and since this imaginary recipe is a part of a comedy it is unlikely to be edible. If you look at other ingredients they can surely make someone sick.
I think the ingredient Silphium described in this dish (Now considered extinct) could be Sea Holly (Eryngium spp). Its highly debated as many authors think it is some extinct variety of fennel, but from the images on the coins it doesnt look like a Fennel.
Don’t worry big companies still can’t copy anything quickly, even with AI. Why? Because before they can ship a single feature, they’ll need to schedule 42 alignment meetings, debate AI-generated slide decks, and log their “strategic pivots” into an AI-curated Jira board.
The real moat isn’t just code it’s speed, focus, user trust, and the ability to actually ship. Those are things bloated orgs struggle with, with or without AI. If you’re solving a real problem and building a real brand, you’re already ahead.
WoW, i stand corrected. Though my actual point was that now we have Plutonium and it cant be wished away it cant be put in silos, even if we lock it up in silos sooner or later say in a few centuries when people will forget about it those silos will leak and threaten humanity. There is no better way to get rid of it than spent it away in fast breeder reactors. It will threaten humanity sooner or later.
If they are real slime balls they can justify it by saying you see we use speculative decoding so we first use a smaller faster model model first and then then answer is enhanced by larger model blah blah ..... "FOr the best User experience"
Its the router they are using, we surely are not getting what we select. Also after a few queries the intelligence drops. abruptly. and doesn't recover even after we start a new session, so there is another internal quota at play.
There should be a law that lawmakers can only be scientific people when it comes to science, i.e scientist's and engineers not humanities or arts majors. These people take decisions which are absolutely absurd. The entire western world has stockpiles of plutonium which is not going to be used for anything other than mutual self destruction. Because of these anti nuclear activists types the western hemisphere has trillions of dollars energy locked in the plutonium bombs, that could have been used in Fast breeder reactors and would have benefitted humanity.
Claude is overrated premium piece of developer tech, i have produced equally good results from Gemini and Way better with GPT - medium. And GPT Medium is a really good model at assembling and debugging stuff than Claude. Claude hallucinates when asked why something is correct or should be done. All Models fail equally in some or the other aspect, which point to the fact that these models have strength's and weaknesses, and GPT just happens to be a good overall model. But dev community is so stuck up on Claude for no good reason other than shiny tooling : "Claude Code", besides that the models can be equally worse as the competition. The Benchmarks do not explain the full story. In general though the Thumb rule is if the Model says you are Brilliant, Thats genius or Now thats a deep and insightful question you asked... Its time to start a new session.
I consider Apple to be practical, Also Apple will be running Gemini on its own hardware. This is better than Buying perplexity and running chinese model on which Perplexity runs. Training Models is a money on game, Its better to rent models than training your own. If everyone is training models they are going to be come commodity, also this is not the final architecture.
In a world where Crabs are trying to rewrite everything in their favourite Crab Speak its nice to see the Reverse. I wonder if it coulkd be used to translate Rust compiler itself to C :-D
Sure but trying to close source what has been opensource for a decade or trying to reduce features is very strange. I thought those people had higher standards.
This is not a world model, this ise at best the reimplementation of the the NVIDIA prior art around NeRF / 3D Gaussian Splatting and monocular depth, wrapped in a nice product and workflow. What they’re actually shipping is an offline asset generator: you feed it text, images, or video, it runs depth/structure estimation and neural 3D reconstruction, and you get a static splat/mesh world you can then render or simulate in a real engine. That’s useful and impressive engineering, but it’s very different from a proper “world model” in the RL/embodied‑AI sense. Here there’s no online dynamics, no agent loop, and no interactive rollouts; it’s closer to a high‑end NeRF/GS pipeline plus tooling than to something like Google’s Genie/2/3, which actually couples generative rendering with action‑conditioned temporal evolution. Calling this a “world model” feels more like marketing language than a meaningful technical distinction.
Infact my definition of a world model is more closer to what Demis has hinted in his discussions, that video gen models like veo are able to intuit they physics from just video trainingdata suggest that there is an underlying manifold in reality that is essentially computable and thus is being simulated by these models. Building such a model would essentially mean building a physics engine of some kind that predicts this manifold.