Poke
I have used the exact sentence “broadcasting into the abyss” hahaha. It feels to me that everything is short lived and context-less
I have no idea how use mastodon effectively :/. Lenny has the advantage of article + discussion so there is a topic to follow. Mastodon/Twitter has always been too chaotic for me. Any advice on how to make it worth it and not just a massive mess x)?
https://pubpeer.com/ mentionned in the article is an interesting website that I will check out. However, peer review is supposed to be done by experts so I’m not sure how this website ensure that :).
I also found https://openreview.net/about interesting as a concept. Although it is a bit nerve wracking to have reviews public.
Such a stupid lie. A lot of policies are based today on this idea of nudges. I know in my company they tried to improve safety mindsets through that « science » and that it is all fake quite literally killed people.
I have no good advice for this but I’m sorry this is happening to you :(. That’s really not fair and very inconsiderate.
I would advise not training your own model but instead use tools like langchain and chroma, in combination with a open model like gpt4all or falcon :).
So in general explore langchain!
merci j’avais pas réaliser ça!
Rocky Linux, AlmaLinux, and Oracle Linux for example.
Pour y aller il y a un train de nuit qui fait Milan Palerme en 20hrs. Pour 100€ l’aller, t’as une chambre privé! Je l’ai pris (avec un arrêt à Rome sur le retour et c’était super sympa. Être en pijama dans sa chambre dans le train, à regarder les montagnes et la nature c’est chouette :)
J’utilisais qwant par principe mais maintenant j’utilise ecosia parce que je préfère planter des arbres et ils allemand je crois :)
Et aussi de Vancouver il y a Squamish et Banff. C’est top la bas :)
Je suis sur téléphone aussi mais j’ai pas eu de problème avec les autres instances.
Interesting article! I wholeheartedly agree with every other topic but I partly disagree on the AI front. AI has a topic is much wider than crypto and nfts, and better defined than the meta verse. It has concrete uses from document extraction, to protein prediction, and data analysis. However, where I agree with the author is that, on platform like LinkedIn, you find so many quacks who are suddenly experts, telling how AI is the game changer that you didn’t know for something completely unrelated. There is a va lot of pseudo science and false (but seemingly logic) conclusions thrown around. And that’s where the gift is: not in the technology, but in the marketing by scammers.
E.g. they keep on pushing that, as an expert, AI will replace you unless you adapt and that only those who use ai will survive. However, early research shows the opposite and that using AI actually help low performers and has little impact for experts. Here is an interesting podcast on it
J’essaye de créer un compte mais ça marche pas :(. Ça me remet la page de signup
I think you are absolutely correct for the interpretation of the photon count :)
I Googled it to see because I thought they maybe were using event cameras then but no, they use 10bit instead of classic 8bit but they are not litterally counting photons (which would not be useful). It’s interesting that it improved the precision and recall of their « object detection model ». Guess the image is of better quality then.
The link from 2 years ago is not particularly impressive: https://arxiv.org/abs/1406.2283 this is an equal valent paper I think from 2014
It’s an interesting discussion thanks!
I know that it can be done :). It’s my direct field of research (localization and mapping of autonomous robots with a focus on building 3D model from camera images e.g NeRF related methods )what i was trying to say is that you cannot have high safety using just cameras. But I think we agree there :)
I’ll be curious to know how they handle environment with a clear lack of depth information (highway roads), how they optimized the processing power (estimating depth is one thing but building a continuous 3D model is different), and the image blur when moving at high speed :). Sensor fusion between visual slam and LiDAR is not complex (since the LiDAR provide what you estimate with your neural occupancy grid anyway, what you get is a more accurate measurement) so on the technological side they don’t really gain much, mainly a gain for the cost.
My guess is that they probably still do a lot of feature detection (lines and stuff) in the background and a lot of what you experience when you drive is improvement in depth estimation and feature detection on rgb images? But maybe not I’ll be really interested to read about it more :). Do you have the research paper that the Tesla algo relies on?
Just to be clear, i have no doubt it works :). I have used similar system for mobile robots and I don’t see why it would not. But I’m also worried they it will lull people in a false sense of safety while the driver should stay alert.
The thing is working good enough most of the time is not enough. I haven’t driven a Tesla so I’m not speaking for their cars but I work in SLAM and while cameras are great for it, cameras on a fast car need to process fast and get good images. It’s a difficult requirement for camera only, so you will not be able to garante safety like other sensors would. In most scenarios, the situation is simple: e.g. a highway where you can track lines and cars and everything is predictable. The problem is the outliers when it’s suddenly not predictable: a lack of feature in crowded environments, a recognition pipeline that fails because the model detects something is not there or fail to detect something there… then you have no safeguards.
Camera only is not authorize in most logistic operation in factory, im not sure what changes for a car.
It’s ok to build a system that is good « most of the time » if you don’t advertise it as a fully autonomous system, so people stay focus.
Money and freedom is quite nice :)