Apart from the actual exploit, it is intriguing to see how a security researcher can leverage an AI tool to give them an asymmetric advantage to the actual developers of the code. Devs are pretty focused on their own subsystem and it would take serendipity or a ton of experience to be able to spot such patterns.
Thinking about this more .. given all the AI generated code being put into production these days (I routinely see posts of anthropic and others boast how much code is being written by AI). I can see it being much, much harder to review all the code being written by AIs. It makes a lot of sense to use an AI system to find vulnerabilities that humans don't have time to catch.
I fear SK is a harbinger of what's to come in other developed western countries. Companies seem to follow each other in getting more out of workers. When jobs and career become the most important thing (for survival, professional satisfaction or lifestyle), then family life suffers. Even with superb (albeit costly) child care that I avail, my wife has to throttle down her career to put taking care of the kids first, while I prioritize income generation. I have to put considerable thought into how I spend quality time with my kids (including taking a risk that a delayed email response will have professional costs for me). But I feel far more fortunate than my wife (who has to pay a heavy toll forgoing her professional aspirations). Society needs to evolve to do better to support working parents and caregivers.
I think small scale entrepreneurship might be a solution to the current corp craziness. Also, need to ensure lifestyle creep doesn't occur. Easier said then done.
I recently got a 5090 with 64 GB of RAM (intel cpu). Was just looking for a strong model I can host locally. If I had performance of GPT4-o, I'd be content. Are there any suggestions or cases where people got disappointed?
I am a manager. It is pretty bad in terms of tracking. Wandb looks great but really expensive (small team in a super large corp, pricing we were quoted plus the challenges of no-saas made this a no go for me). Been trying to get team members to mlflow and some adjacent tools but it is too hard to do it right.
Amazon is the same I think? I live in constant fear we will have a runaway job one day. I get daily emails to myself (as a manager) and to my finance person. We had one instance where a team member forgot to turn off a machine for a few months :(
I get why it is a business strategy to not have limits .. but I wonder if providers would get more usage if people had more trusts on costs/predictability.
Did you buy a home > 10 years ago? Given inflation, isn't your mortgage not easy to pay off at this point (even if you did pay the minimum?). I can imagine one of two scenarios: (a) at the start, you really stretched and got a nice place to live (bravo!! in hindsight that was a genius move as you enjoyed many years of good quality living) or (b) your income has been stagnant (sorry :( )
I got a place 5 years back and did not overstretch at all ... now, the biggest challenge is our place is too small and has other inconveniences (lack of commute) that is painful. Selling and rebuying is trauma I don't want to inflict again.
CS PhD here. I've been involved in deep learning for many years now, and generative AI for the last couple of years. I saw some other major revolutions in my life starting with the Internet/Web explosion and the Smartphone explosion. You can say cloud and social networking were significant events but I would not put them in the same class as the first two. I would put the current embodiment of VR and crypto on an even lower rung of the "society impact" ladder. My personal opinion is that Gen AI tech (particularly LLMs but perhaps also the related stuff - diffusion, MLLMs) are more like Internet and Smartphone as game changers for society. Now, for the Internet boom, there was a ton of hype. I don't recall smartphones being as frothy but maybe I am forgetting the froth that was Angry Birds. So while I agree there is way too much hype at the moment, I think this is going to be big.
Hi .. wondering what the situation is for a senior Canadian scientist wanting to raise funds/do a start up in the US? Had H1B many years ago (and possibly have a year of time left on it .. not sure that matters). Lots of papers so can go the EB1 route if needed. Want something simple and straightforward. Is transferring via existing employer beneficial (with delaying future plans)?
That's pretty weird. Usually, less companies mean less demand for labor. If supply is the same, that means price-for-labor (salaries) would go down. Unless, this was accompanied by people leaving (reduction in supply). Do you have an explanation for this?
Curious about the military job (and other services including Police Departments). Are you eligible for pension/benefits as a presumably civilian subject matter expert? How does one get such a cyber gig?
Spot on. Things are actually MUCH more relaxed in the office, which is why some people don't want it (e.g. people with caregiving responsibility). Everyone I know with children 0-10 wishes there was some more flexibility in scheduling. RTO just steals that from you. It has nothing to do with the amount of work.
For VC funded startups, I would imagine sec 174 is less bad. For bootstrapping, I just can't imagine how to make it work. A Canadian company can hire globally without the craziness of this amortization too.
I'm reading about the founding story of many startups .. at the early stage when they had few users, there was no moat. Success seems is a big moat. If this guy had taken venture financing(I know this wasn't a thing back then but humor me), trademarked milkbar, peppered ads everywhere, it isn't inconceivable that he'd get to 500 stores. Would that have led to lasting success? Unclear.
I think a wider issue I'd like to see a discussion on is the current workplace. I think employers are pushing individuals and teams beyond their limit - what are you going to do? Quit in this job market?
I'm literally doing the math on what sort of pay/title cut I'd be willing to take to move from a large corp to a sane, non-toxic workplace. I'm mid-career and know some people my level who have just exited the rat race. I was hoping once US rates get cut, things get less meaner .. but looks like this will continue for a while longer.
As it stands, tech at large companies has become a terrible career. I'm saying this as someone who is deeply passionate about technology and work at the cutting edge of AI. I think a big part is cargo culting and MBA-think in management. Instead of working, we spend months and months planning to do work. Other people in this boat or just my pond?
Back when I was in undergrad, I recall how I was taught C. Just read one of the bible books on a weekend, and was ready to go. I was recently taking a look at Kotlin books and literally banged my head on the table. I realized the language has a good rap but it is ridiculously feature-laden .. to the point they threw in the kitchen sink. A key positive of languages is easiness to learn. I really wonder about Kotlin. It may be well-designed, but did it really need to be so big?
I'm also curious if it is just me. I am a grey hair now, with many other responsibilities. Why were C, Python and Go so easy for me when kotlin seems so hard to penetrate (for me)? Is there a way to quantify language complexity?
Scientist here and have book marked this article for close reading (so apologies for this question if it is discussed in the article).
I had a few brushes in RL (with collaborators who knew more RL than I did). A key issue we encountered in different problem settings was the number of samples required to train. We created a headless version of the underlying environment but could not make it go a lot faster than real-time. We also did some work to parallelize but it wasn't enough (and it was expensive). Is the TM related RL training happening in real-time or is it possible to speed it up? That seemed like the key problem to make RL widely used, but curious about your thoughts.
Ac actual academic career is the WORST in terms of burn-out. I was writing paper reviews at 4am. People I know who are professors board planes with a pile of papers to read or review. Midnight meetings to discuss conference organization. Add in the pressure of publish or perish.
Thinking about this more .. given all the AI generated code being put into production these days (I routinely see posts of anthropic and others boast how much code is being written by AI). I can see it being much, much harder to review all the code being written by AIs. It makes a lot of sense to use an AI system to find vulnerabilities that humans don't have time to catch.