Fascinating Guardian profile of Song-Chun Zhu, a leading AI scientist who left UCLA for China after nearly three decades in the US. He argues that today’s AI, dominated by large neural nets and benchmark-driven research, has drifted away from the deeper pursuit of intelligence — reasoning, causality, social and physical understanding. Zhu says China offered him resources and freedom to chase these harder, less fashionable questions, while US academia felt increasingly constrained by political pressure, funding structures, and a preference for “safe” incremental work.
Raises two questions: Are we losing diversity of scientific thought by letting scale-driven AI monopolize the field? And what does it mean for global research leadership if the next big paradigm shift in AI comes from outside the US?
I don’t see gorillas.bas — that was my favorite. I actually found my appreciation for writing code modifying lines of code in that game to make bigger explosions.
nibbles was my favorite. Reading the code as a 13 year old I learned that they doubled y resolution by using lower and upper square ascii characters. It inspired me to find creative solutions for problems.
I just finished listening to it on audible. It is certainly thought provoking, but full of contradictions as others have mentioned. Namely that this technology cannot be contained, and yet that it must be contained is pretty doom and gloom. The prognostications about artificial intelligence are hardly as scary as the ones made around genetic sequencing — that you can buy a device for 30k that will print pathogens and viruses for you out of your garage. That’s some scary stuff.
You can buy plasmids and make whatever bacteria you want for a few decades now. AI may help, but it certainly doesn't cost $30k to cause mischief.Pretty sure I learned that in Bio 102
I just want to echo this here and in a bit different wording: AI will provide step-by-step guides on how to make viruses that just about any idiot can follow, for very cheap, and in under a year time frame.
I really really hope I'm missing something big here.
Having a step-by-step guide and actually being able to follow it are two very different things. If you follow YouTube channels like The Thought Emporium you'll see how hard it is just to duplicate existing lab results from published sources in biology. To go a step further and create new dangerous things without also getting yourself killed in the process is a pretty tall order.
We should be talking about the more abstract problem of asymmetric defense and offense.
Imagine that nukes were easy to make with household items. That would be a scenario where offense is easy but defense is hard. And we would not exist as a species anymore.
Once a hypothetical technology like this is discovered one time, it's not possible to put the genie back in the bottle without extreme levels of surveillance.
We got lucky that nukes were hard to make. We had no idea that would be the case before nuclear physics was discovered, but we played Russian Roulette and survived.
So put a hundred more in series and you get bigger voltage. If 10 of them lit a LED, which needs something like 1.5V then 100 of them would give you 15V. Car batteries are 12V or 24V, depending on the car model/size, so 100 or 200 in series and you get that covered.
It's a beautiful thing if it can bring humanity together towards a common aim.
But if it leads to the collapse of monetary systems, the collapse of civil society, looting, rioting, the rise of nationalism, and WWIII that's most certainly going to lead more death and destruction than the virus itself.
Way to escalate the situation. Let's see how well quarantine measures work and how the next 4 weeks pan out with the economy in hibernation.
It will cost us dearly but I wouldn't say it's going to lead to rioting and WW3. If anything, this is a global problem for which we need global solutions and not fucking nationalism merely 100 years after it already screwed our societies.
Let's hope that China will enforce prohibition of wild animal trade/use as much as possible. It's not in the CCPs interest to let that kind of instability rain down on it.
Introduction to Computer Science followed by Data Structures and Algorithms should give you a healthy start.
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Learning these fundamentals is useful, but not necessarily immediately practical. Building and doing is the best way to learn. This is a good start, and the fundamentals will certainly give you an edge against most people graduating from a bootcamp, but after this I'd recommend finding a good tutorial, whatever the language that teaches you step by step how to build XYZ... I learned ruby/rails by doing Michael Hartl's tutorial building a microblogging platform like twitter.
You have one of the best universities in the world sharing their material for free. That's what's valuable, not the forums that can be attached to the platform or the certificate that no employer cares about.
I mean the professor or university could be the best in the world in terms of scientific discovery or university rankings criteria and this does not mean these materials are necessarily the best learning experience.
Did you even take courses there? Have a different experience?
The best part is, that unlike medical or law you can also do it from virtually anywhere.
I have been doing some semblance of programming since I was 8 years old (now 39). I think it’s one of those things you kind of have to have a passion for or you can easily get burned out.
But I also think it’s one of those things that are more in demand than ever. If I was laid off I’d have to question why I was working for the company in the first place and didn’t see it coming. There are quite literally 7-8 LinkedIn messages from recruiters almost daily. I’m not sure many attorneys or physicians can say that. And when you are in demand like that you’re constantly leveling up your salary every few years.
Finally, I know or very few professions where every 3-5 years you need to completely have learned something new to stay ahead of the game. When I was 8 I was doing q-basic. I’ve had to learn over 12 languages since then.
> I'm not sure many attorneys or physicians can say that
As someone who worked as a lawyer for 6 years before switching careers to software (after 4 years of self-teaching, mind), I can say that in the one year I've been professionally employed as a dev, I have already received several multiples of the number of recruiter messages during the totality of my time practicing law.
As someone who has lived out of AirBnB for almost 3 years traveling all around the world and never once being scammed, I find the title of this article to be a bit alarmist.
AirBnB has host and guest verification options. If Becky and Andrew don't have their identities verified via drivers license but manage over 90 properties that is your first red flag right there.
Second, if the host can't accommodate you you reach out to AirBnb and put the onus on them to find you an acceptable property that meets your standards. You don't let the host offer up some random place that happens to be available, that's suspicious.
I've had a number of hosts cancel on me at the last minute recently, I didn't immediately jump to the conclusion that it must be a scam. I simply assumed that their property is also listed on VRBO and other sites and someone either beat me to the punch or they got more money, or they didn't realize that they can't list the unit and forgot to take down the listing.
Mistakes happen. Sure, there are scammers out there on every platform, but in my 3 years and over 100 successful stays, I really find this article's title tough to swallow.
I really enjoyed reading this article as a way of reevaluating my approach to gender inequality, but I have a problem with the title and main premise.
Why do you need to have a daughter to support gender equality? Aren't these values equally as important to instill in your sons? Aren't they values we should embrace regardless of whether or not we have children?
Raises two questions: Are we losing diversity of scientific thought by letting scale-driven AI monopolize the field? And what does it mean for global research leadership if the next big paradigm shift in AI comes from outside the US?