ryoroke785

CS academia is dead. So where does that leave AI PhDs like me? Did my ICLR reviewer bidding today. Skimmed a few abstracts, and the methods are the exact same recipe I learned when I got into 3DV two years ago. Swap in a newer video gen base model and boom, new paper 🥲 Makes you wonder how many of the 60k submissions were actually thought up by AI. Meanwhile, World Labs' Atlas has basically solved 4D scenes. Academia is so far behind it's not even funny. I still remember the day GPT-6 Astra dropped. My feed was flooded with GPT + Blender doing inverse graphics and GPT driving robot arms through manipulation tasks. The results were so good I literally had to sit down. A year ago, I was dead sure LLMs could never have spatial intelligence. A year later, Astra slapped that belief right out of me 💀 There's no doubt Astra was post-trained on tons of 3D and manipulation data, and it's only going to get bigger and faster. To me, that means any domain that can be represented symbolically, with clean benchmarks for RL, is going to get swallowed by LLMs. Next to real LLM intelligence, most academic papers that add a bit of inductive bias and tune their way to SOTA are just roadkill waiting to happen. Sadly, these papers keep piling up and flooding every conference. It's inertia, plain and simple. We've been chasing SOTA for so long that it's hard to stop overnight. But make no mistake: the paradigms in a lot of areas converged long ago. What used to be research is now pure engineering, and the room for academics to add inductive biases is only going to shrink. So as a PhD student, I see two paths left. One: if you can't beat them, join them. Clean data, build infra, then go to industry and train foundation models. Two: go back to real science. Stop caring about squeezing out another 0.1% on a benchmark, and start asking why this works and that doesn't, with foundation models themselves as the object of study. As a friend put it: AI research might end up looking more and more like biology, except the organisms are silicon-based 🤣 Beyond these two, it's hard to see anything that won't get eaten by LLMs. Still, I'm pretty pessimistic. I can feel the value of human knowledge being eroded bit by bit. Everyone will get their own AlphaGo moment. What will academia even look like after this... 😭

xjincaox's tweet photo. CS academia is dead. So where does that leave AI PhDs like me?

Did my ICLR reviewer bidding today. Skimmed a few abstracts, and the methods are the exact same recipe I learned when I got into 3DV two years ago. Swap in a newer video gen base model and boom, new paper 🥲 Makes you wonder how many of the 60k submissions were actually thought up by AI. Meanwhile, World Labs' Atlas has basically solved 4D scenes. Academia is so far behind it's not even funny.

I still remember the day GPT-6 Astra dropped. My feed was flooded with GPT + Blender doing inverse graphics and GPT driving robot arms through manipulation tasks. The results were so good I literally had to sit down. A year ago, I was dead sure LLMs could never have spatial intelligence. A year later, Astra slapped that belief right out of me 💀

There's no doubt Astra was post-trained on tons of 3D and manipulation data, and it's only going to get bigger and faster. To me, that means any domain that can be represented symbolically, with clean benchmarks for RL, is going to get swallowed by LLMs. Next to real LLM intelligence, most academic papers that add a bit of inductive bias and tune their way to SOTA are just roadkill waiting to happen.

Sadly, these papers keep piling up and flooding every conference. It's inertia, plain and simple. We've been chasing SOTA for so long that it's hard to stop overnight. But make no mistake: the paradigms in a lot of areas converged long ago. What used to be research is now pure engineering, and the room for academics to add inductive biases is only going to shrink.

So as a PhD student, I see two paths left. One: if you can't beat them, join them. Clean data, build infra, then go to industry and train foundation models. Two: go back to real science. Stop caring about squeezing out another 0.1% on a benchmark, and start asking why this works and that doesn't, with foundation models themselves as the object of study. As a friend put it: AI research might end up looking more and more like biology, except the organisms are silicon-based 🤣 Beyond these two, it's hard to see anything that won't get eaten by LLMs.

Still, I'm pretty pessimistic. I can feel the value of human knowledge being eroded bit by bit. Everyone will get their own AlphaGo moment. What will academia even look like after this... 😭

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ryoroke785 retweeted

Sam Padilla

@theSamPadilla

3 days ago

After 2+ years in the robotics data space, we are shutting @Eidon_AI down. The thesis was right. But the business is brutally hard. We close this chapter by open-sourcing everything we built and sharing lessons for anyone venturing into the space. https://t.co/pyL9IkjQPT

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ryoroke785

@ryoroke785

3 days ago

ひまわりのお揃いもいい感じ、背面も見惚れる。ピンクの衣装も全部違って。

ryoroke785

@ryoroke785

3 days ago

衣装はいいですねえ。白いブラウスの模様に惹かれていました。ブローチのようなアクセサリも。

ryoroke785

@ryoroke785

3 days ago

くるみやまびこ、くるみっこ。普通のくるみパンも美味しい

ゆい｜海運女子

@yui_journey

3 days ago

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ryoroke785 retweeted

voxium

@v0xium

5 days ago

Super long post ahead: This resonated with a lot of people. We are all facing similar kinds of experiences in our work environments. Many suggested that I take it easy, just use LLMs to finish whatever task I have, get the paycheck, and be happy. I understand that sentiment. However, there comes a point in your life when you need to find meaning in your work. It gets boring to do the same thing again and again. Your brain needs stimulation. You will start finding it somewhere if not in your work. But what if you do not have the time? How will you find your purpose then? Quitting is not an option. You need that money. There are bills to be paid. So then, the option is to just hide your face in the dirt and do what is asked of you. Nobody will be there to listen to you. And why would they do that? The end goal of any business is to become profitable. And how will you do that? Ship faster, see what gets more users onboarded, retain them. Repeat. There is no concept of soul in this process. There is no one who will care about your satisfaction. Just you. Find it somewhere. Code in your free time. You do not have free time. Find it. There is no other option. You want to feel something? Build it in your free time. I agree with a lot of people here saying we will just be meat proxies. Tbh, I do not understand the term exactly, but I think I get the sentiment. But on the other hand, what I worry about is that a lot of engineering domains will start lacking intellectuals. Think about it. If you are a kid now, in school or college, all you need to do is ask LLMs to finish your homework. Teachers are aware of it, and there is nothing they can do. If I were a kid, LLMs would be my greatest friend. They would be my replacement for the hatred I had for assignments. The art of learning will eventually disappear. Who will be there to teach, and who will be there to learn? Eventually, we will have a generation of kids who have no drive and curiosity. But I am pretty sure that if we steer this technology in the right direction, the opposite could also be possible. I just do not see that happening anytime soon. I digressed a bit, but what I am trying to say is that software engineers used to take a lot of pride in their work. There is still a possibility for that, but an MBA can now come to you and say, "Hey, I could have shipped that too. What have you done here?" Are we ready to face that question? I think not. That is ego. That will eventually go away as we adapt. Some of us are already adapting. There is resistance, and there always will be. I think it is a natural progression during any technical revolution. Yes, it is a big leap in technology. We cannot deny it any longer. What I am interested to know is how this will translate to other domains. Software can be automated. Let us assume that. What happens to math, physics, biology, medicine, mechanical engineering, aeronautics, and so on? Will they face a similar fate? I do not have an answer to that. Okay, now coming back to the topic. What do you think will happen to devs? Since most of us, judging from the response to this post, are using LLMs to do whatever management asks, what will happen to us? If models become super good, which I think they eventually will with the pace at which we are moving forward, will all of us eventually go out of a job? I again do not have an answer to this. Can someone focused solely on engineering survive? Can someone focused solely on design survive? What about someone focused just on PM? Can an individual do the job of all three? Maybe eventually they will have to. So how do I see the future of software engineering now? I think I need to reference the replies I have received on this post. It is bleak. At least the future of what we think of as traditional software engineering is bleak. I am not even sure whether whatever comes next can be considered software engineering or not. On a side note, I never even liked labeling building software as engineering. When I was a kid, I always associated engineering with making things like bridges, cars, rockets, etc. So how will you find the hard problems to solve when you are not getting any time in your day apart from talking to Claude? I do not know where we will find that. Maybe I need to pick up a new domain. Hardware? Very interesting, but I am too dumb to learn about it now. And most probably, it is not going to pay my bills. So not that. And there is nothing else that comes to my mind apart from these two. I think I am doomed. I know I am just rambling in this post. Not a lot of it will make sense, but I need to just get it out. Now, regarding this post, this is a once-in-a-lifetime reach I got on this one. I do not think this will happen again for a long time. Almost everyone on the tech side of X saw this and shared their opinions. I am grateful for this. This single post almost tripled my followers overnight. I am thankful to all of you for sharing your thoughts on this matter. I would like you all to post more on X. Share your thoughts. It can be about anything. Maybe this will give your brain the stimulation that coding at work is not going to. Start today. Post anything. Try to be original. I could just keep on writing. I like writing. I like writing long posts, even if nobody is going to read them. Maybe that is what I like the most about X. Just sharing my thoughts and seeing what others say about them. Interesting era that we all live in. I could say anything, and hundreds of people are going to see it. Okay, what else? Let us talk about life now. I think, as I mentioned, the soul-sucking nature of AI is something that bothers me. I would have loved AI to solve cancer. It took my grandparents from me, and if it solves that, I do not think anybody would be as happy as me. I need it to create more medicine, help humans live longer, and improve our quality of life. Software automation is fine, but most of our world can live without our CRUD apps. What it cannot live without is new medicine and cures for new diseases. I hope AI gets so advanced that any disease can be cured using personalized medicine. Not sure if I am making sense. Anyways, this technology has had the most impact on my life. And this will continue to happen. I hope that we humans are a part of this industry shift. I do not want to be sidelined. I want to cherish new technology. Do you know how it would have felt to live during the space race? I want to feel something similar. The difference is that the space race was not threatening anyone's livelihood. On the other hand, this time, all we hear from the AI industry is that they are going to make us jobless. I hate that about them. So negative. It does not have to be like that. I am tired of typing this now. I will share my thoughts sometime later. Yes, I do have many thoughts. That is all I do. I think about anything. At least no one is automating my consciousness yet.

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