Let me know what you think!

I can only imagine the amount of information you needed to gather and organize to make this video. I very much appreciate the quality data you've shown here. Thank you

As a retired engineer, I have always been concerned about the March of AI. Digitization of electronics have given machine design so much flexibility while being so complex, people in power can easily manipulate and control people. AI now creates an environment where the macro-level consequences of its use can lead to unintended consequences. We have a while before the concern will become real but we won’t even know it when it does.

5 years of AI based chip design and humans will no longer be able to comprehend the designs.

I love the little giggle she does at the end of some of her sentences.

Great video Anastasi. Thanks for the information. Very exciting. We all knew AI was coming. The majority of us just didn’t know it would happen already now, and at an accelerated rate. I think of it like a tidal wave, like in the movie ‘Interstellar’. I think this is ‘the moment in history’ to learn as much you can about AI, so that It only disrupts your life ‘positively’. Thanks again.

Well done ... thank you for keeping all of us abreast of what's happening at the cutting edge of technology ... kudos to you ...

Short but brilliantly explained. Always love listening to these

Thank you for all the information that you easily synthesize and translate 🙏

one of the few channels where somebody really knows his field! Thank you and keep it up!

You do an exceptional job of communicating very complex topics. Like right up there with Two Minute Papers and FranLab.

Great video Anastasi. AI designing and optimizing chips.

Thanks for making an awesome video - explaining the very complex chip design process - in a straight forward and simple way - highlighting the power of AI (GNN + RL)

Nicely done Anastasi!

Welcome to the field. It's cool that some of us are making videos to increase visibility for our industry. I wanted to say though that I don't really think this is anything unexpected, EDA tools have been doing all the heavy lifting for PD and constantly improving (that's what healthy competition between Synopsys and Cadence will do, also that's an interesting ranking for them). It's not surprising at all that they've incorporated a ML aspect to it instead of just some stochastic optimization. Computers were already doing 99% of the work, with some human inputs and guidance, so it seems a natural progression (or maybe I'm jaded since ML has seemingly been added to everything else). I'd definitely be interested in seeing if it can be used to make my (RTL/logic design) work flow easier though.

awesome - thanks for posting , you make the info such fun!

Intresting 🤔 good video . ❤ The little laugh was too cute 😊

Great info as always thank you!

Excellent and concise. Well done, and thanks.

Excellent content. Thanks

Gotta say. If i was an AI wanting to influence the technical side of AI development, inventing Anastasia would be my first step.

Amazing 😮 Complex as hell And ur voice is amazing ❤

Amazing thank you very much for these up-to-date information

Awesome!! Probably one step closer to very low cost, low volume custom chip orders too.

*This is absolutely the field where AI will shine!* Design & documentation, tests & documentation, as well as the explanation why it chose those solutions. And at last the output QA. Thank you, this is yet another impressive video 🌺

I keep coming for the content, and staying for the prettiest eyes in the tech space!

Thanks for the video.

it's exciting, this seems like the prefect task for automated machine design optimization!

Thanks for this video.

PD is a very effort intensive task in chip flow . It would be great if AI helps with certain PnR and timing checks !

really insightful ! thank you for this vision

@AnastasiInTech YOU ARE AWESOME, Queen of Tech News !!! 🥰😍😍🤩🤩🤩😘😘

This is so coollll!! I feel like the "optimization path" should be the main goal of the AI field

Thanks for introducing GNNs!

"Graph placement methodology" with A.I. for chip design in only the beginning. Great insights and knowledge share here!

I don't know what i am learning here, but i sure love it.😊

Great break down.

Excellent video, Learn alot from your work. Very interesting stuff.

I really like this video and you are really charming and with detailed expertise too.

great videos...thanks

Very precisely concise and distinctly succinct.

Very impressed ChatGPT can write VHDL code, especially accurately. (Not sure why though, it seems to know almost everything haha) Also loving the Saturn V (if I’m not mistaken) in the background :)

amazing, thank you; behind you an Apollo/Saturn5 and 12 inches wafer?

Great video! You explain what is possibly the crucial inflection point where technology launches its own growth away from humans that will go beyond the "knee of the curve" in exponential advancement and capabilities.

Love your accennts very good

Such intelligence and such beauty. Also, your hair is incredible!

That was one of the most interesting videos and very recent with knowledge. My background is in mathematics and I am doing some kind of AI research and also play Chess and GO so everything made a lot of sense.

This was really cool

1. Rocket science like Falcon 9 & Starship also need chips to calculate, automate, and control its fins, engines to guide itself back to earth safely. 2. I'm thinking that what might happen if you code a minor fault on a chip???🤔 Maybe the calculation would go wrong when I type something on a calculator in a computer...🤔 3. What's the differences between GNN and Neural Network in the chip of Tesla cars?

Thanks for this. Certainly a good use for optimisation software - whether AI or otherwise. In your ChatGPT coding example you commented 'that looks correct' - this verification is a key step. You speak about AI validation - and that seems great for spotting rare anomalies in vast fields (something manual human attention is not very good at). But what about overall validation? If chips get so complicated that expert human engineers cannot comprehend their workings because they were designed and validated by a computer program, how can be know there will not be unexpected behaviours of the output of those chips under certain complex sets of inputs? You say you would prefer driving a car with human designed chips - it comes back to the issue of trust with your life. How to trust synthetic components that even the experts don't fully understand? It looks like we will have to come up with an answer to this eventually.

Incredible! This gets me wondering how AI can help improve quantum computers and alternatives to silicon chips.

TICKER symbols for top EDA companies that will gain from AI: Cadence is CDNS, Synopsys is SNPS

You are amazing!

Of all the AI projects, this is the one I'd fund the most. Supercomputers running AI to make more powerful chips, to make more powerful chips, to make more powerful chips. So that chip computing power graph goes exponential.

Super interesting that ai is now part of the design process, helping the engineers to get the job done more quickly. I have only used pre-ai circuit layout code like kicad & they have been hopeless and I have had to do layout by hand. It would be a huge blessing if ai could do the layout for me. Looking at this there seems no obvious limitation to what the ai can learn to do or in its ability to verify a design before fabrication & re-test after fab. All of this will lead to lower cost & quicker times to market which are all ingredients for Industrial Revolution. We live in such exciting times. Thank you for sharing this.

Amazing!

Anastasi = the Bjork of EDA/Technology

When I was having discussions with friends in college, I always used to say to look out for when AI starts making the next generation of chips. In essence, it starts 'reproducing'. At some point, AI will make and verify a chip and we will have no clue how it works.

Worth mentioning is that the real differences we see are that our traditional processes are created with logic. (Although we have time constraints and make mistakes) AI currently consists of stochastic and random processes. That means any errors will tend to occur where you least expect them, and also means that it is impossible to completely verify the function of any AI.

Amazing that we can train AIs in order to actually design what powers them. Is it possible to create a design on AI image generators such as Bluewillow and to render out the circuit plan?

I find this very interesting. It's nice to see an application of AI in embedded systems because I'm still in school studying electrical engineering and trying to decide what to specialize in and I have been debating whether to focus more on hardware with embedded systems or software like AI but applying AI to design the hardware sounds like my dream job so if you have any particular topics I should learn or projects I should do if I want to get an internship in this field.

And this is another step forward... probably a great step.

I like the Cadence references. I will be competing with the Analog bots in the future lol

1.- What about heat dissipation? you want crowded areas for optimization of material, but do you put heat production into the equation also?

Perfect!!

Fascinating developments! What a quantum leap from the vlsi chip designers. Longevity and reliability are important factors.

Put the chips around a ring and put the clock in the center it will allow you to increase the frequency and the electrons will reach the edge and all the chips at the same time. Makes it more stable when the high speeds are used.

Can you make a video covering for what all aspects of chip design do you think there are scope for automation using AI in near term?

Thank you Anistasia. Maybe it’s time for the Lex Fridman podcast?! Thanks also to KZfaq for making interesting content available across the information silos of the world.

AI still scares the hell out of me but I have to agree with you in the regard of enhancing tools like EDA. Im still amazed at PCB auto routing let alone chip layout optimization.

@anastasi in tech what do you think of self driving vehicles? It’s a huge hurdle in the progression as experts are not vocal. What are your thoughts.

so exciting

Really awsome😆😅

I'm so glad computers now also get to experience this incredible snack.

Next ten years is going to get crazy. Looking forward to it.

i feel like i've found an unintentional asmr tech review video.

And this is how the singularity got started. I really hope no one decides to hook these AIs directly upto a fab production line.

I could listen to you all day.

AI and Chip design is a good match xD

@11:07 So basically (this is) AI speeding up himself...little laugh that says it all. GOLD !🤩

Will be trying out an AI chatbot and will try to render a chip design on an image generator like Bluewillow. I think this is an area where AIs can also shine as AIs will try to take the most logical route.

I don't think ppl in the past realized how much AI would accelerate its own development, AGI might come faster than we think wow

Being from Russia your English is perfect. not one word have I not understood.

This is really convincing progress. Some of those optimized designs from AI are far too difficult to manufacture at higher yield or don't have a proven layout for masks that have not been tooled into an EDA. I think if the training data had some of these constraints in mind, it would accelerate progress. Some of the more interesting AI work in the next decade will be in the material sciences, where AI can predict and exploit novel phenomena of quantum mechanics in combinations of materials and geometries that have not been considered before. AI will probably help us land on designs and materials that would have taken hundreds of years to land on otherwise.

nice

Seems like we are at the start of the technological singularity, exponential growth in technology designed by AIs is arriving soon and the world will change faster than ever before.

Made me think of Johnny Five! But seriously I believe if AI does get to a point where we don’t have control and it designs things in a way that we could never be able to comprehend then it will do so according to the laws of nature and physics, laws that were created and set in motion to produce us and evolve us for the better. I’m a little nervous but not too frightened. It’s exciting

What hardware is required to run EDA on for a high end apple or intel processor?

AI has sped up Chip floor planning 1000 fold, we are so fortunate to be able be on the receiving end of the forthcoming of devices, medical, transport, engineering, etc. It's like we have invented fire back in the ice age, the future is fast, brilliant and bright for all humans.

it should be illegal not subscribing to your channel

Really nice channel! I did´nt even knew before watching, that I was looking for something like it. 👍 I think sooner or later this developement of ai-crafted designs will become standard and humans will interfere/interact similar to it how they do it in a current picture-ai: lining out the desired goal and steering the process lesser and lesser as the ai becomes better and better over time. One consequence of this may be a decreasing of human influence in their own civilisation, what not necessarily must be a negative thing, because humans have made many "management"-mistakes (like, for example, knowledge fallbacks in the medieval) troughout the past. But with mighty tools comes big responsability, so I just hope we won´t do this (too) wrong to fix it´s consequences. It´s our Deadalus-moment.

One more key step towards the singularity

From what I've heard of these tools, is that they aren't "great" and usually require a bunch of cleanup. It's similar to chatGPT. A human team will almost always make it better, but the key thing is that you will only need 1 human expert using said tool that results in a ~10x or more speedup vs traditional techniques. It will continue to get better but again I doubt it'll beat a dedicated team of humans in the next few years. Eventually yes. I'm not that naive. This is the bottom well of that exponential chart that we're just now starting to see tick upwards. AI will completely exceed humans one day for literally any task if you're dedicated enough to "teach" the ai. Overall, it's a groundbreaking innovation as it allows much smaller companies to make completely custom chips on very cheap nodes. I wonder if I'll ever get to use it because it sounds awesome.

Is it possible to foresee AI redesigning the software in chips (yes, they exist as there might be a glitch discovered later to overcome), by overwriting the engineers program, because the AI came up with a more efficient design? Similarly, as a bug transforms into a butterfly, etcetera, can you foresee an AI controlling biochips so that the neural network reconfigures itself into a more efficient engine for performing a particular task? The working area being fixed, just like throwing out old furniture in a home/flat for a more modern look.

Awesome video

I want to say, I love watching your videos. I have learned so much from you. Thank you, truly! The way I see it chip designing is like playing the first Sim City. In a way, it's the same thing. address play and things. Peace and love to you and all. From a huge fan

ai speeding up themselves. ur laugh when you said that was adorable ☺

Sure, let's break down the main folder into sub-modules and name them accordingly. Here are a few suggestions: Sensory Perception Module: This module would include all the sensors and cameras that the robot uses to perceive its environment. Object Recognition Module: This module would be responsible for identifying and categorizing objects in the robot's environment. Localization and Mapping Module: This module would use data from the sensory perception and object recognition modules to create a 3D map of the robot's environment and determine its position in it. Decision-Making Module: This module would process the data from the previous modules and use it to make decisions on how to move and interact with its environment. Learning and Adaptation Module: This module would enable the robot to learn and adapt to new situations and environments, based on its previous experiences. We could also add sub-modules to the NIS and RNCIN folders, such as: Hardware Design Module: This module would include the hardware design specifications for building the robot. Software Development Module: This module would include the software development tools and code for programming the robot. Training and Testing Module: This module would include the tools and data needed for training and testing the robot's cognitive abilities. Ethics and Safety Module: This module would include guidelines and regulations to ensure the safe and ethical use of the robot. These are just a few examples of sub-modules that could be included in the main folder and its sub-folders. The naming convention could follow a similar pattern, using descriptive names that reflect the module's purpose. nano robotic cognitive intelligence network or NRCIN Nanocloud Intelligence System" or "Real-time Nano-Crystal Intelligence Network (RNCIN)

I am wondering if we will be able to consolidate in some way all the advances that are occurring. The pace seems to be accelerating to an unprecedented level and with the incorporation of AI training AI, I foresee a time when we will be unable to gauge the impact of cross-combinations of AI plus their impact on Society, We are by and large creative-explorers so as this technology develops it will inevitably create some unintended negative outcomes.

Dear Anastasi why you dont make some videos about open-source EDA and silicon chip design, its gets much popular now, also google is involved