OpenAI researchers warned board of AI breakthrough ahead of CEO ouster

Not at all; just that the ‘understanding’-related content of pure mathematics is much less evident on the page. It mostly lives in the heads of mathematicians and is largely independent of notation, whereas writing blocks of code is a task that is literally about using notation — something for which a huge amount of high-quality training data exists. Of course, the higher level ideas in programming and software development are not just about ‘writing code’ itself, but I suspect this is where current models begin to show their weakness.

As long as your checks clear and the HVAC in the data center holds up I think you're good to go.

The beauty of the Assistants is you're not limited to OpenAI models. You can wire them up to any model anywhere (out they can wire themselves up), so you can have specialist threads going for specific functions.

That's absolutely true.

But

They have leaked real things in the past, in exactly the same way. It may be 5% or less that turn out to be true, but there's the rub. That's why no one can completely dismiss it out of hand (and why were even discussing it on an HN comment thread in the first place).

I mean, I'll take this seriously when there's something more substantive than zero meaningful search results and a /pol/ post to evaluate it against.

Right now it reads like something a moderately clever shitposter would invent - if there was a letter, why not just leak the letter? - and while everyone's clearly very excited over the events of the past week, I'd like to hope epistemic personal hygiene has not been entirely abandoned.

One more interesting thing.

Here is how GPT-4 performs long multiplication: https://www.phind.com/search?q=multiply%2012.23341%20by%20-1...

Here is how GPT-$ Turbo performs long multiplication: multiply 12.23341 by -123.23354 using long multiplication method. To multiply 12.23341 by -123.23354 using the long multiplication method, we first ignore the decimal points and treat the numbers as integers. We'll reintroduce the decimal point at the end. Here's the multiplication step by step: ``` 1223341 (this is 12.23341 with the decimal removed) × -12323354 (this is -123.23354 with the decimal removed) -------------- 1223341 (multiplied by 4) 0000000 (multiplied by 5, shifted one position to the left) 1223341 (multiplied by 3, shifted two positions to the left) 3660023 (multiplied by 3, shifted three positions to the left) 4886682 (multiplied by 2, shifted four positions to the left) 0000000 (multiplied by 2, shifted five positions to the left) 1223341 (multiplied by 1, shifted six positions to the left) 1223341 (multiplied by 1, shifted seven positions to the left) 0000000 (multiplied by 2, shifted eight positions to the left) 0000000 (multiplied by 3, shifted nine positions to the left) -------------- 15077944092654 (sum of all the above products) ``` Now, we need to place the decimal point. The original numbers had 5 and 8 decimal places, respectively, so the result should have 5+8 = 13 decimal places. So, 15077944092654 becomes 1507.7944092654. Since one of the original numbers was negative, the result is also negative: -1507.7944092654

Therefore, 12.23341 multiplied by -123.23354 equals -1507.7944092654.

Compare with correct result: -1507.5664205714

Here is how I experimented with long multiplication on GPT-4 a month ago (5 shot, GPT-4 made mistakes on addition in 3rd some time 4th digit, regardless of decimal point position):

Multiply -0.9923 by -0.9923 using long multiplication.Solution: multiply individual digits in reverse order, increasing the order of magnitude of the result for each next digit in the first number : 3310*(0+0)=9, 3210*(0+1)=60, 3910*(0+2)=2700, 3910*(0+3)=27000, 3010*(0+4)=0, step's subtotal[0]=29769; 2310*(1+0)=60, 2210*(1+1)=400, 2910*(1+2)=18000, 2910*(1+3)=180000, 2010*(1+4)=0, step's subtotal[1]=198460; 9310*(2+0)=2700, 9210*(2+1)=18000, 9910*(2+2)=810000, 9910*(2+3)=8100000, 9010*(2+4)=0, step's subtotal[2]=8930700; 9310*(3+0)=27000, 9210*(3+1)=180000, 9910*(3+2)=8100000, 9910*(3+3)=81000000, 9010*(3+4)=0, step's subtotal[3]=89307000; 0310*(4+0)=0, 0210*(4+1)=0, 0910*(4+2)=0, 0910*(4+3)=0, 0010*(4+4)=0, step's subtotal[4]=0; Sum of partial results: 29769+198460+8930700+89307000+0 = 98465929. Set the decimal point position in the result by adding the decimal places of both numbers (4+4=8), counting from the right. Final result: -0.9923*-0.9923=0.98465929

I was able to tune the LLaMA 2 with QLoRA to produce viable results only with precision up to 4th digit after decimal point, however difference in length of mantissa cases wrong result.