That's laughable in 2025, and together with the wimpy 153 GB/s memory bandwidth (come on, Strix Halo is 256GB/s at a fraction of the price!) they really don't have a leg to stand on calling this AI-anything!
As pointed out in other places as well a better comparison will be the upcoming Pro & Max variants.
Also, as far as I know, Strix Halo mainly uses the GPU for inference not the little AI accelerator AMD has put on there. That one is just to limited.
I'm saying this is pretty weaksauce for AI-anything in 2025, especially considering the price tag. Sure, there will be later models with more memory and bandwidth (no doubt at eye-watering prices), but with 32 GB this model isn't it.
I'm sure it's a perfectly fine daily driver, but you have to appreciate the irony of a massive chip loaded to the gills with matrix multiplication units, marketed as an amazing AI machine, and yet so hobbled by mem capacity and bandwidth.
The best way to phrase this would be, information seeking as a form of procrastination itself.
I first remember reading this phrasing here on HN and I've been using it for years to explain to others that what I am doing is not "work", its just a hobby.
Every time this topic comes up on HN, I always like to remind readers about the following:
One of my favorite facts ever is that Voyager 1 contains something called the Voyager Golden Record [1]. It has the following quote written:
This is a present from a small, distant world, a token of our sounds, our science, our images, our music, our thoughts and our feelings. We are attempting to survive our time so we may live into yours.
I thought it was interesting to share the full quote. It’s a fascinating read.
>An official statement by President Jimmy Carter was included as images (positions 117, 118). It reads, in part:
This Voyager spacecraft was constructed by the United States of America. We are a community of 240 million human beings among the more than 4 billion who inhabit the planet Earth. We human beings are still divided into nation states, but these states are rapidly becoming a global civilization. We cast this message into the cosmos…
It is likely to survive a billion years into our future, when our civilization is profoundly altered and the surface of the Earth may be vastly changed. Of the 200 billion stars in the Milky Way galaxy, some – perhaps many – may have inhabited planets and space faring civilizations.
If one such civilization intercepts Voyager and can understand these recorded contents, here is our message: This is a present from a small distant world, a token of our sounds, our science, our images, our music, our thoughts, and our feelings. We are attempting to survive our time so we may live into yours. We hope some day, having solved the problems we face, to join a community of galactic civilizations. This record represents our hope and our determination and our goodwill in a vast and awesome universe.
The Golden Records [1] seem like astonishing, singular undertakings to me. Like the Svalbard seed bank, or the LHC, or the Prado. Their existence inspires me because they remind me of what we're capable of.
The book Murmours of Earth by Carl Sagan, Frank Drake, and Ann Druyan is an interesting commentary on the ideas and choices behind the production of the Golden Records. Published in 1978, but there are copies available from the usual aources.
Genuine question: what is so great about the Golden Record?
I understand the Svalbard seed bank. That can come very handy in a bad situation. May we never need it. I have visited the LHC and it is seriously impressive. Works in the Prado are amazing.
But the Golden Record feel just like someone made a mixtape and then chucked it far away. The music on it of course is great. But will anyone ever find it? And even if anyone ever finds it, will they have the anatomy to listen to it? If we received a similar record could we do anything with it?
For example the recorded greatings. A few sentences in many languages. There is something there. Presumably an interested alien could use it kind of like a Rosetta Stone to learn the structure of our languages. But for that to realistically work they would need a lot more recording in each language and the speakers should be saying the same thing!
Similarly the “brain recording”. An hour long recording, “compressed” somehow and then bandwidth gated so it can be etched into a disk. How is that supposed to contain any usefull information? It is like you want to transmit the content of a book, so you take a blurry underexposed image of the book’s spine as it is reflected in a foggy mirror. Even if the aliens are brilliant there is not much they can do with that “brain recording”.
The whole thing is so vibes based, but on the rational level it doesn’t add up to much.
Your skepticism about the Golden Record is understandable, but its value goes beyond mere practicality—it's a powerful symbol of humanity's hopes, dreams, and curiosity.
Sure, the odds of another civilization discovering and fully decoding it are slim. But the Record was never simply meant as a practical tool, like the Svalbard seed bank or the LHC. Instead, it's an intentional gesture of optimism, an attempt to capture and communicate the essence of who we are at this unique moment in our history.
Importantly, the Golden Record was carefully designed using universal scientific principles—binary notation, hydrogen atom properties, and pulsar maps—ensuring that any intelligent civilization might realistically decode it. The instructions etched onto its cover rely on fundamental concepts universally understandable across the cosmos.
The greetings, music, and even brainwave recordings aren't strict instructions but rather snapshots showcasing humanity’s diversity, creativity, and complexity. Even partial understanding by an advanced civilization would provide profound insights into human emotion, ingenuity, and our deep desire for connection.
In the end, the Golden Record is NOT just about practical outcomes; it's about reflecting humanity’s best qualities back to ourselves and inspiring us to strive toward the ideals we've shared with the universe.
> Importantly, the Golden Record was carefully designed using universal scientific principles—binary notation, hydrogen atom properties, and pulsar maps—ensuring that any intelligent civilization might realistically decode it. The instructions etched onto its cover rely on fundamental concepts universally understandable across the cosmos.
Both the Golden Record and the Pioneer Plaque were carefully crafted with universality in mind, drawing on fundamental scientific principles understandable by any intelligent civilization. They both shared many similarities. [1][2]
> Some images contain indications of chemical composition. All measures used on the pictures are defined in the first few images using physical references that are likely to be consistent anywhere in the universe.
> The pulsar map and hydrogen molecule diagram are shared in common with the Pioneer plaque.
[1] Explanation of the Voyager record cover diagram, as provided by NASA
In my very first Astronomy class, just a few years after voyager, I did a report on that record, based on a cartoon: "Send more Chuck Berry."
It is an extraordinary piece of work of human history: THank you Astronomer Carl Sagan, Linda Salzman Sagan, Frank Drake, Ann Druyan, Jon Lomberg, and others.
Can confirm, this isn't just an IT thing. Physicians are a prime example—people tend to put doctors on a pedestal, and some doctors start believing they know everything about everything, even when it's clearly outside their wheelhouse. Being smart in one area doesn’t automatically make you an expert in another, but it’s easy for everyone involved to forget that.
I’m a CFO that used to work in healthcare. Have had many cases where a doctor tries to explain to me how accounting “should work” and I have to tell them we have this little thing call revenue recognition or GAAP or how accruals work, etc. basically the stuff covered in accounting 101.
I’m used to fielding questions about numbers from all types but only doctors will immediately jump to telling you it’s wrong without asking questions and adamantly insisting they know the right way to do things is what I’ve noticed as a personality quirk generalization.
Slightly off-topic but I worked at a UK research organisation that was a privatised entity recently spun-off from a civil-service organisation. The new CEO (who came from a finance background) got a tour of each department. He apparently listened to all of the tech evangelism from the department directors and then asked them how their department's accruals were doing. Those department directors who asked him to clarify what he meant by accruals didn't stay in post very long. Allegedly.
This is a bit extreme. I've worked in many industries where the word 'accrual' is kind of internal to the finance/accounting department. I'd estimate over 70% of very good functional department heads I've worked with in the past would ask for clarification too. If they were still confused after further clarification or weren't able to comeback with an answer, then there is a bigger problem potentially with their ability to own a budget/manage spend.
This is kind of like punishing someone for not knowing your preferred buzzword. I've seen dozens of times that when a new high ranking person joins, their language quickly starts to become the defacto language of the org. If they like the "headwind" "tailwind" terminology, then it becomes what people everywhere start writing in the slides and how they discuss items of risk. You shouldn't be punishing people for asking for clarification (and there certainly a whole group of people that like to ask versus sitting silently then looking it up later). Hopefully there was more too it.
Oh nice. A culture where asking questions is punished. If this was a problem don't fire people. Train them. Make sure everyone does required training. If they refuse then you may have a case for PIP.
Otherwise it is just landmine driven performance
Rant not at comment! But the situation of the comment. Hope it worked out for you!
I'm a retired neurosurgical anesthesiologist; you are correct about this illusion that physicians often labor under. But it's worth noting that when medical topics are posted here, the responses from non-physicians are sometimes so nonsensical that I for one laugh out loud reading them. In fact, I look forward to these discussions for this very reason.
The worst thing is, most doctors aren't even smart in their own domain. They are nothing more but trained monkeys who follow a flow chart that has drug sales at the end.
Great insight—thanks for sharing. It strikes me that bureaucracy is inherently self-perpetuating- once established, it rewards compliance over creativity, steadily shifting the culture until innovation becomes the exception rather than the rule.
Perhaps the real challenge isn't balancing innovation and marketing—it's creating a culture that genuinely rewards bold ideas and meaningful risk-taking.
> [Bureaucracy] rewards compliance over creativity
Imho, this is the wrong takeaway from parent's point.
Bureaucracy rewards many things that are actual work and take time. (Networking, politicking, min/max'ing OKRs)
Creativity and innovation are rarely part of the list, because by definition they're less tangible and riskier.
A couple effective methods I've seen to fight the overall trend are (a) instill a culture where people succeed but processes fail (if a risky bet fails then the process goes under the spotlight, not the person) and (b) tie rewards to results that are less min/maxable (10x vs +5%).
It seems most organizations naturally become more risk-averse as they age and grow since the business becomes more well-defined over time and there is more to lose from risky ventures. The culture has to reward meaningful risk-taking even when that risk-taking results in a loss, which can cause issues when people see the guy who lost a bunch of money getting a bonus for trying (not to mention the perverse incentives it may create).
I spent time working with Andrej and the rest of the FSD team back in 2020/2021, and we had plenty of conversations on how human visual processing maps onto our neural network architectures.
Our approach—transformer-based attention blocks, multi-scale feature extraction, and temporal fusion—mirrors elements of the biological visual cortex (retina → LGN → V1 → V2 → V4 → IT) which break down raw inputs and integrate them over time. It’s amazing how closely this synthetic perceptual pipeline parallels the way our own brains interpret the world.
The key insight we discovered was that explicitly enforcing brain-like topographic organization (as some academic work attempts - such as this one here) isn't necessary - what matters is having the right functional components that parallel biological visual processing. Our experience showed that the key elements of biological visual processing - like hierarchical feature extraction and temporal integration - emerge naturally when you build architectures that have to solve real visual tasks.
The brain's organization serves its function, not the other way around. This was validated by the real-world performance of our synthetic visual cortex in the Tesla FSD stack.
We can think of a solution space, with potentially many good solutions to the vision problem, and we can, in science fiction-like speculation, that the other solutions will be very different and surprise us.
Then this experiment shows its solution is the same we already knew, and that's it.
Then there aren't many good potential solutions, there is only one, and the ocean of possibilities becomes the pond of this solution.
The convolutional kernels in the first levels do converge to Gabors like the ones in V1 (and there were math works in the 90-ies, in neuro research, about optimality of such kernels) so it wouldn't be surprising if higher levels would converge to something that is similar to the higher levels of visual cortex (like hierarchical feature aggregation that is nicely illustrated by deep dreaming and also feels like it can be optimal under reasonable conditions and thus would be expected to emerge).
Did you read the part where he explicitly mentioned that they discovered how enforcing that architecture was not necessary, as it would emerge on its own?
Unlike neural networks the brain contains massive numbers of lateral connections. This, combined with topographical organization, allows it to do within layer temporal predictions as activations travel across the visual field, create active competition between similarly tuned neurons in a layer (forming natural sub networks), and quite a bit more. So, yeah, the brain's organisation serves it's function, and it does so very very well.
They probably don’t. They’re very different. LLM’s seem to be based on pragmatic, mathematical techniques developed over time to produce patterns from data.
There’s at least three fields in this:
1. Machine learning using non-neurological techniques (most stuff). These use a combination of statistical algorithms stitched together with hyperparameter tweaking. Also, usually global optimization by heavy methods like backpropagation.
2. “Brain-inspired” or “biologically accurate”algorithms that try to imitate the brain. They sometimes include evidence their behavior matches experimental observations of brain behavior. Many of these use complex neurons, spiking nets, and/or local learning (Hebbian).
(Note: There is some work on hybrids such as integrating hippocampus-like memory or doing limited backpropagation on Hebbian-like architectures.)
3. Computational neuroscience which aims to make biologically-accurate models at various levels of granularity. Their goal is to understand brain function. A common reason is diagnosing and treating neurological disorders.
Making an LLM like the brain would require use of brain-inspired components, multiple systems specialized for certain tasks, memory integrated into all of them, and a brain-like model for reinforcement. Imitating God’s complex design is simply much more difficult than combining proven algorithms that work well enough. ;)
That said, I keep collecting work on both efficient ML and brain-inspired ML. I think some combination of the techniques might have high impact later. I think the lower, training costs of some brain-inspired methods, especially Hebbian learning, justify more experimentation by small teams with small, GPU budgets. Might find something cost-effective in that research. We need more of it on common platforms, too, like HughingFace libraries and cheap VM’s.
