FODMAP stands for fermentable oligosaccharides, disaccharides, monosaccharides, and polyols. FODMAPs generate gas as side effect of being fermented in the gut. Most people just pass this gas, but for some people, usually people with irritable bowel syndrome (IBS), it can be very uncomfortable and amplify their other IBS problems.
People who are suffering from pain and bloating with no obvious cause may be advised to go on a low-FODMAP diet for a few weeks to see if their symptoms go away.
I've wondered about this. Do we really know enough about what the human brain is doing to make a statement like this? I feel like if we did, we would be able to model it faithfully and OpenAI, etc. would not be doing what they're doing with LLMs.
What if human cognition turns out to be the biological equivalent of a really well-tuned prediction machine, and LLMs are just a more rudimentary and less-efficient version of this?
Yes, we do. Humans share the statistical association ability that LLMs possess, but also conscious meaning and understanding. This is a difference in kind and means that we can generalize beyond the statistical pattern associations that we've extracted from data, so we don't require trillions of examples to develop knowledge.
Theoretically a human could sit alone in a dark room, knowing nothing of mathematics and come up with numbers, arithmetic algebra, etc...
They don't need to read every math textbook, paper, and online discussion in existence.
Pre-training is not a good term if you are trying to compare it to LLM pre-training. Closer would be the model's architecture and learning algorithms which has been designed through decades of PhD research, and my point on that is that the differences are still much greater than the similarities.
So I'm not disputing this, but I set up a similar scheme to the author almost 8 years ago and conduct 90+% of my online business through the custom emails. Everything from Amazon to small local business.
In that time I have had 'leaks' twice: my State's Fish and Wildlife licensing organ, and GitHub. In both cases I assume it's more that the email ends up being public, not because of something like Apollo.
I guess it's possible that spam is getting filtered before it ever hits my inbox.
Edit: I was responding to the idea of it leading to spam, not that Apollo wasn't collecting information on me.
For those curious: I signed up with Apollo and looked at what they had on me (via the link in the flagged/dead post by fontain). The email address they have is technically correct, but it's a non-current work email. It's still active and I do get a lot of senseless/bizarre business sales inquiries on that address. The phone number they have is wrong and I don't recognize it. They have my LinkedIn byline; it's likely how I was 'found' so quickly, as my username is the same there. I'm listed as cold.
I used to do the same until I got tired of it. The only two leaks I found were United Airlines and Gary Johnson, the Libertarian presidential candidate, who sold my email to the Scott Walker campaign (strongly confirming my suspicions that Republicans use libertarianism as a gateway drug).
Does it solve anything? I don't see this as a GitHub problem, it's a "we built a dependency management system with untrusted publishers" problem.
GitLab's `include` feature has the same concern. They do offer an integrity check, but it's not any more capable than hash pinning to a commit.
Fundamentally, if you offer a way to extend your product with externally-provided components, and you can't control the external publishers, then you've left the door open to 'these issues'.
This boils down to a security via obscurity argument. Is obscurity a useful tool? Often, yes. Should you depend on it? Definitely not. Is it annoying to lose? Yes.
That could be addressed with a small NVMe heatsink. They're available and their use is advised already for NAND PCIe 4.0 and 5.0 hardware, but they would fit the Optane use just as well.
Flock cameras aren't enforcing anything. They collect your license plate and distinguishing details of your car. It's just car X with plate Y detected at location Z at time T.
Notably, they are not used for speed detection or 'good driving' detection.
You might think that having a constantly-present, objective, impartial camera enforcing a law is better than a sometimes-present, subjective, often not impartial beat cop doing that. But that's not what Flock does. Flock just turns that 'sometimes-present' beat cop into an 'always-present' beat cop, without addressing any of the other beat cop problems.
This looks like another AI project. The HN user is new, the GitHub user is 4 days old, and all the content in the GitHub repo is authored by someone else. There's a blog repo with one commit containing 29 pre-written posts. A third repo 'nexusai-landing' is the only repo where 'denisepattenson' has committed anything.
Yeah, I second this. Like other comments have mentioned, you'd expect a human to add a video to such a post. I wonder what urged this robot to post this to HN.
The other code author is a "Dr. Josh C. Simmons" whose GitHub profile leads with "Building AI systems and influence architecture at scale." and "Founder @ Meridian Strategic Systems — Running experiments in cognitive systems, behavioral modeling, and automated influence generation."
So, my guess is that this a prototype of whatever Meridian is going to be doing.
People who are suffering from pain and bloating with no obvious cause may be advised to go on a low-FODMAP diet for a few weeks to see if their symptoms go away.