I don’t know if the spec supports that on its own. Although, it’s a good feature request.
You’d have to update the WG configuration each time a new IPv6 address connected. So, you would probably need to connect through something like a client that could push a config update and restart the service.
Not impossible, but that’s another layer of complexity to maintain.
I’m not aware of any specific films we were in. We filmed a lot of our robotics trials for various collaborations, but no documentaries while I was there. Shortly after I left, my team got some acclaim for their Lunar Ark project (which is really cool). But, I had been out for a couple of years by that point. If they filmed a documentary, it likely would have been for that project.
Yeah. Almost all of the "killer apps" for LLMs all revolve around generating content, images, or videos. My question is always the same, "Is there really such a massive market for mediocre content?"
Yep. I think this is right on. The anthropomorphization in their behavior and problem descriptions is flawed.
It's precisely that analogy we learned early in our study of neural networks: the layers analyze the curves, straight segments, edges, size, shape, etc. But, when we look at the activation patterns, we see they are not doing anything remotely like that. They look like stochastic correlations, and the activation pattern was almost entirely random.
The same thing is happening here, but at incomprehensible scales and with fortunes being sunk into hope.
I feel like this fails on the premise that the models can be improved to the point where they are reliable. I don't know that holds true. It is extremely uncommon that making a system more complex makes it more reliable.
In the rare cases where more complexity produces a more reliable system, that complexity is always incremental, not sudden.
With our current approach to deep neural networks and LLMs, we missed the incremental step and jumped to rodent brain levels of complexity. Now, we are hoping that we can improve our way to stability.
I don't know of any examples where that has happened - so I am not optimistic about the chances here.
My graduate research was in this area. My lab group developed swarm robots for various terrestrial and space exploration tasks. I spent a lot of time probing why our swarm robots developed pathological behavioral breakdowns - running away from construction projects, burying each other, etc... The issue was so fundamental to our machine learning methods that we never found a way to reliably address it—by the time I left, anyway. No matter how we reconfigured the neural networks, trained, punished, deprived, or implemented forced forgetting or fine-tuned, nothing seemed to eliminate the catastrophic behavioral edge cases—nothing except for dramatically simplifying the neural networks.
Once I started seeing these behaviors in our robots, their appearance became much more pronounced every time I dug deeply into proposed ML systems: autonomous vehicles, robotic assistants, chatbots, and LLMs.
As I've had time to reflect on our challenges, I think that neural networks very quickly tend to overfit, and deep neural networks are incomparably overfitted. That condition makes them sensitive to hidden attractors that cause the system to break down when it is near these areas - catastrophically.
How do we define "near"? That would have to be determined using some topological method. But these systems are so complicated that we can't analyze their networks' topology or even brute-force probe their activations. Further, the larger, deeper, and more highly connected the network, the more challenging these hidden attractors are to find.
I was bothered by this topic a decade ago, and nothing I have seen today has alleviated my concern. We are building larger, deeper, and more connected networks on the premise that we'll eventually get to a state so unimaginably overfitted that it becomes stable again. I am unnerved by this idea and by the amount of money flowing in that direction with reckless abandon.
We sure did. About 60-70% of all of the world's opium was sourced from Afghanistan until 2022. That supply was used to make actual prescriptions in non-OECD countries - like India & China - as well as sold to make heroin in the US, EU, Asia, and Africa.
But be careful about confusing cause & effect. The cause of the Afghani farmers growing opium was the insatiable demand for opium that was developed through legal means. Then, when countries like the US started to restrict access to opiates, addicts and patients alike started to seek alternatives to the scarce prescriptions.
More to the point, why didn't patients use something else? Because there is nothing. Purdue's misinformation actively discouraged the discovery of new non-addictive compounds for decades. No one was looking, and the R&D pipeline ran dry.
By the time enough doctors sounded enough alarms to cause a change in the late 2010s, research in non-addictive pain management solutions was decades behind. No one engaged in it because there was no need for it. Now that we realize it was all a lie and these drugs have killed millions, there are no alternatives. Very few potential compounds are even in Phase 2 clinical trials right now, let alone the half dozen that would be needed in Phase 3 to ensure we have a single alternate choice for pain management in the next five years.
So, the outlook looks bleak. Today, in 2024, we don't have good ways to manage pain that is non-addictive, and certainly no good way to reach the millions who are hopelessly addicted to opioids for pain management. But, very little of this is the patient's fault - and a lot of this is directly related to the monumental efforts of Purdue to misinform for profit.
That doesn’t clarify anything about your knowledge. The specialized hospital cleaning crews are in the ER every day and dozens of hours per week in the OR, but that doesn’t allow them to practice medicine or perform surgery. Proximity is not the same as practice.
The medical practice (until a few years ago) was profoundly and intentionally misinformed about the addictiveness of Oxycodone and Oxycontin. You brought up a question about why people didn't learn from the Opioid Wars, but your flippant question could just as easily be applied to the MDs who wrote the prescriptions.
Medical doctors are smart; they MUST know about the Opioid Wars and the horror the opium wrecked on Chinese society for centuries. Why would they prescribe such a dangerously addictive compound to injured and vulnerable people having the worst day of their lives?
Instead, you blame patients with little choice (or capacity to evaluate choices) in a terrible situation. And, if you talked to any addicts, you'd sure find that the top of the "victim totempole" is actually really crowded with people who got there the exact same way. That is no coincidence.
The fact of the matter is that Purdue intentionally misinformed everyone - doctors, patients, caregivers, and family. They used marketing, propaganda, bribes, recognition, and myriad other tools to convince everyone that their product was different. Doctors, knowing full well about the Opium Wars, wholeheartedly believed the propaganda. I wasn't the first patient to be discharged from the hospital with a multi-month supply of opioids. This was a common practice.
The worst part is for someone who claims to be around addicts, you think I am somehow unique in my story. My story is so mundanely typical that it should be nauseating. Medical treatment is, by far, the most common way addicts start with opioids. 75% of all heroin users whose addictions started in the 2000s reported that it began with prescriptions from their doctors.
I genuinely suggest you spend some time talking to the addicts around you rather than judging them. You'd quickly come to regret the flippancy of your statement and probably have some empathy for their situation. These were regular people with jobs, families, lives, hopes, and dreams. In a crisis, they entrusted medical doctors to make the best medical decision for them, and the price they paid was their future.
What are you talking about? Where was America getting their opioids before The Sacklers? Go ahead and pull a chart of heroin deaths vs. years and draw a vertical bar on where Purdue launched their widespread marketing misinformation and disinformation.
This is the largest and most deadly episode of addictiveness since the tobacco companies were marketing cigarettes as healthy. If this were a fire, you’d be arguing:
“Look, America has always had fires. Sure Purdue started fires in all 50 states that spread into the forest, but they were small when Purdue started them. Now, there is a blaze that has spread uncontrolled across the Continental US. So, obviously there were other parallel organizations starting fires.”
No. That doesn’t follow. Purdue stared the fires. They added tinder with marketing misinformation, then they inhibited any attempt at controlling it with active disinformation campaigns to confuse doctors and regulators about the root cause. Now, it’s a wild uncontrolled inferno, but they started the first fires.
That’s gotta be the most ignorant opinion I’ve heard on the subject. This clearly is coming from someone who has had the benefit of good health, or hasn’t had the misfortune of a critical ER visit.
When I got addicted to opioids, the doctors didn’t ask me what I wanted in the ER. I got Dilauded as they prepped the OR. I wasn’t lucid enough or cognizant enough to give informed consent. During my recovery, there wasn’t an option of alternate anything - I got a lot of morphine and then oxy. I was discharged 4 weeks later from the hospital with a 3 month prescription for 120mg of opioids per day. That would kill most people.
My story is not unique. It is so common it could be a troupe. The doctors saved my life in one way, then discharged me into a hell of addiction that it took 9 months of serious determined effort to overcome.
Then, some uninformed keyboard warrior like yourself comes along and blames people in my situation? Maybe you should have read a little less Opioid Wars and a little more Current Events. You clearly know nothing about this problem.
I run the ML team at a larger unicorn. I fully agree with this. We are multi & hybrid cloud with global SD Wan and everything on CI/CD. There is still a ton of maintenance, patches, deployments, and updates that require us to manually intervene in our otherwise automated systems.
If OP were to learn sys admin skills, CI/CD, and Terraform, he would be a key candidate for any ML team globally. They’re all going in that direction. We work closely with Google and they coached us in that direction. Sys Admin skills will always be in demand.
Pick a good IDE, set it to the most pedantic mode you can, and work on the code until there are no errors, no warnings, and only acceptable info notifications.
Have a good test suite with realistic scenarios. Add more to that all of the time.
Get outside feedback on whether you documentation and diagrams are readable and keep them up to date.
If you can do that, you can write mission critical code.
Becareful with Stelara. The body reuses the same inflammatory cytokine group that is the target in the lungs to fight off infection. So, your lungs can’t fight infection very well on Stelara small issues can very quickly become life threatening.
I got Pneumonia that turned into Sepsis in about 60 hours. It happened so fast that the doctors brought in an addiction specialist. The only other time they’ve seen this is when drunks pass out and aspirate on their vomit. (Crohn’s doesn’t let me drink, so we can rule that out…) After days of studies, we found the warning label on Stelara about the elevated risk of lung infections. My care team reached out the Janssen and confirmed it. After about 4 days of IV antibiotics, I was sent home to continue on oral antibiotics.
Still, if I die from something like this, it’s still worth it to take these biologics. At least I lived a much better life for a while thanks them. The side effects can be life threatening, but the ability to have a life is worth it.
TLDR: On Stelara, I went from Pneumonia to Sepsis in about 60 hours while taking oral antibiotics. The warnings on the labels of the biologics are serious - and the side effects can be life threatening.
Wouldn’t an environment that has a significant sulfuric acid content naturally also a relatively limited free oxygen?
I’m thinking of Venus. That sort of environment would satisfy all criteria and would also start to get into the temperature ranges that would make Si-Si bonds possible.
That would at-least bracket the types of planets and their history to a useful extent.
Silicon has almost the exact same properties as carbon. At high temperatures, carbon chains can’t form, but silicon chains can. In a high-temperature or high-pressure range, silicon might for a basis for life, analogous to carbon for us. So, not only was that question not stupid, it was profound.
Look at silicon on the periodic table. All of the things that make carbon great, basically silicon has almost exactly, except it needs a high temperature for most of those properties to be expressible.
That teacher didn’t know what he was talking about. Ridiculing a student for questions is such detestable behavior. The silliest questions can end up being the most insightful. I really despise teachers like that.
Here is a paper all about how your question was actually wonderful.
On the contrary, make all of your passwords “DROP TABLE users;”. You’ll quickly sort out which passwords are being handled so insecurely by your vendors. This would mean they both don’t sanitize user input and don’t hash or otherwise obscure your password. They are a menace to society.
There is no legitimate reason for that. Your washing machine is infected and part of a bot net. Contact LG and get them to help you reset and secure it. You might also want to take a look at all of your devices on your home internet. It seems attackers have gotten into your internal network.
That premise alone should make us question everything about that ridiculous movement. Today’s LLMs have access to almost all of the accessible data on the web we have generated to date. AGI is going to have the SAME data to work with - adding whatever amount we generate between now and then.
There isn’t a hidden data cache that is not being dug up and incorporated into today’s latest LLMs - and none of them have embarked on a quest of vengeance. The premise of AGI getting uncontrollably smart by absorbing internet data is wholly flawed. We’ve already absorbed almost all of it and nothing happened.
You’d have to update the WG configuration each time a new IPv6 address connected. So, you would probably need to connect through something like a client that could push a config update and restart the service.
Not impossible, but that’s another layer of complexity to maintain.