2016 ?????
A DARPA Perspective on Artificial Intelligence [pdf]
31–40 of 64 posts
Re: A DARPA Perspective on Artificial Intelligence [pdf]
#32Earlier quoted context omitted.
Theranos got a great deal of funding too, and the truth about how none of the "Second Wave" ML self driving car technology comes even remotely close to safe self driving will be coming out probably later this year. The issue is that ML has no conceptual and causal understanding of anything. For confirmation, I've been carefully watching the countless "self driving" startups in San Francisco driving around, and I have…
None of those self-driving MLs have a virtual world model in their "head", right? They just react to the latest video frame. If so, it's not even a fish level intelligence, it's more like a house plant.
All of the self driving systems I have intimate knowledge of have some level of "persistent memory". It dramatically improves performance in a lot of common situations, e.g. you're coming up to an intersection and your view of stationary cross traffic is occluded by a bus/truck. You enter the intersection and now the planner has to decide whether that vehicle is on an intersection path with the SDC. You only have a few frames of information without persistence and the velocity error might still be large. Thus the safety system has to slam on the breaks to avoid a collision that will never actually happen, potentially causing a real accident if the car behind is following too closely.
Re: A DARPA Perspective on Artificial Intelligence [pdf]
#33FYI the presentation is from December 2016.
I was gonna say this seems really outdated. 2016 was ages ago in the AI world. We've had Openai Five, AlphaStar, MuZero, BERT, GTP and tons of other groundbreaking stuff since then. This presentation tells you nothing about the current state of the field.
Re: A DARPA Perspective on Artificial Intelligence [pdf]
#34Earlier quoted context omitted.
Theranos got a great deal of funding too, and the truth about how none of the "Second Wave" ML self driving car technology comes even remotely close to safe self driving will be coming out probably later this year. The issue is that ML has no conceptual and causal understanding of anything. For confirmation, I've been carefully watching the countless "self driving" startups in San Francisco driving around, and I have…
None of those self-driving MLs have a virtual world model in their "head", right? They just react to the latest video frame. If so, it's not even a fish level intelligence, it's more like a house plant.
If youre curious, Cruise has a fairly comprehensive (but long) overview of their tech that goes over their world model and world simulation stuff: https://youtu.be/uJWN0K26NxQ
So no, its a bit more than a house plant
Re: A DARPA Perspective on Artificial Intelligence [pdf]
#35I wonder who is trying to get what funded? "Second wave" is going gangbusters, despite Gary Marcus' every-six-months rant; the review of statistical learning is reasonable given a barely technical audience, but the summary of "third wave" seems designed to extract large amounts of funding from people who aren't up to date on the state of the field.
Theranos got a great deal of funding too, and the truth about how none of the "Second Wave" ML self driving car technology comes even remotely close to safe self driving will be coming out probably later this year. The issue is that ML has no conceptual and causal understanding of anything. For confirmation, I've been carefully watching the countless "self driving" startups in San Francisco driving around, and I have…
You can't always tell whether the car is operating autonomously even from the back seat, let alone another vehicle. A lot of operators keep their hands very close to the wheel and follow its motions to minimize response time when they need to take over.
I've worked at companies whose vehicles you've probably seen and have never heard anything like what you're suggesting is "the truth". Can you provide more details on how current solutions don't remotely approach reasonable safety levels?
Re: A DARPA Perspective on Artificial Intelligence [pdf]
#36I wonder who is trying to get what funded? "Second wave" is going gangbusters, despite Gary Marcus' every-six-months rant; the review of statistical learning is reasonable given a barely technical audience, but the summary of "third wave" seems designed to extract large amounts of funding from people who aren't up to date on the state of the field.
Theranos got a great deal of funding too, and the truth about how none of the "Second Wave" ML self driving car technology comes even remotely close to safe self driving will be coming out probably later this year. The issue is that ML has no conceptual and causal understanding of anything. For confirmation, I've been carefully watching the countless "self driving" startups in San Francisco driving around, and I have…
> The issue is that ML has no conceptual and causal understanding of anything
Practitioners work with much more tightly defined objectives and methods for improving their systems than "conceptual and causal understanding of anything". From the perspective of folks in the industry we've been making remarkable progress, well beyond what we could have expected. We're saturating major benchmarks, sometimes in one to two years. Back in the day, during the "AI Winter", it was often 10 years before a new breakthrough happened.
Re: A DARPA Perspective on Artificial Intelligence [pdf]
#37The most pressing dangers of AI most researchers see:
- error rate too high
- you can trick a classifier with noise
- it's racist sometimes
Actual dangers of AI:
- stop problem
- infeasibility of sandboxing
- difficulty of aligning black boxes with human values
Re: A DARPA Perspective on Artificial Intelligence [pdf]
#38Here’s the presentation in video form with a bit more context & detail.
Re: A DARPA Perspective on Artificial Intelligence [pdf]
#39It's good to see a main funding agency's perspective. As a researcher, I like their non-hype way of defining AI as "programmed ability", which is accurate and realistic -- also puts AI further apart from real intelligence, which means unanticipated activities. I would like to know more what they see as "abstracting", from their perspective. We haven't got much further in our scientific understanding of intelligence -…
> As a researcher, I like their non-hype way of defining AI as "programmed ability", which is accurate and realistic
This is the first point of advice in the Heilmeier Catechism
Re: A DARPA Perspective on Artificial Intelligence [pdf]
#40"Contextual adaptation" is what they want, but that doesn't mean it's coming in the near future. However, this does mean that funding for research on it will be available. As I've said for years, the big lack in AI is in the "common sense" and unstructured manipulation area. Nobody can build something with squirrel levels of manipulation and agility, even in simulation. Robot manipulation in unstructured situations i…
This is one of my favorite little videos to illustrate the dichotomy - https://i.imgur.com/o7lI08Y.gifv
For all of our mastery of information processing, our ability to fabricate and motivate fine differentiated structures is really quite incredibly poor relative to biology. The little beetle is basically alien technology relative to the toy. But add in the fact that it can feed itself, repair itself and reproduce itself with a system that can scale 3-5 orders of magnitude up and down based on need is pretty mindblowing.
The mRNA vaccines might be one of the first times where we've leveraged biology to directly fabricate a discrete part with desired properties. Certainly in raw tonnage of output I can't think of anything that comes close. I feel like this is only going to advance with time, to the point where we may be growing robots instead of milling and printing them.