skolos

Interesting - in my setup (llama.cpp rtx5090 qwen-3.6 27b) prompt processing with mtp is almost half vs non mtp. Sounds like I need to investigate what is wrong.

"Multi-token prediction gives a free speedup of up to 2x on many models" - at the expense of halving prompt processing speed

deterrent - no one starts war with a country that has nukes

There was lots of discussion within Russian and Ukrainian war analytics that nukes (at least tactical) are useless in this war for the following reasons:

- they would not change much on battlefield - there is no large concentrations that you can nuke - everything is dispersed

- nuking urban centers again won't change much on battlefield but would alienate China

- Russia's equipment is known to be not most reliable/maintained and worst that can happen to Russia is them trying to nuke and nukes not working

It sounds more like market based allocation than gameification.

I'd say adding another 16Gb gpu would be worth it - you'd be able to run larger model/larger context all within gpu's. It would give you more options of what you can run fast. Your current model probably doesn't run completely from GPU (depending on quants I don't think you can squeeze Gemma4:26b into 16Gb vram), so you already have some layers running on gpu and some on cpu. If you add another gpu you might be able to move all layers to vram which should speed up things for you. The layers calculations happen on whatever gpu's it sits, so the layers that are already on your rtx5080 would compute same, but the layers that currently your cpu handles will be computed with faster vram/compute of rtx5060.

The Department of Defense said the xAI data center powered by the gas plant is critical to national security, revealing Grok was used to fire thousands of missiles in the Iran war.

How many times did you try? Same model running multiple times can produce both very good and very bad results. In my benchmark even 10 runs often not enough to tell for sure if one model is better than another.

I like Mathematica and use it regularly. But I did not see any benefits of using it over python as a tool that Claude Code can use. Every script it produced in wolfram was slower with worse answers than python. Wolfram people are really trying but so far the results are not very good.

Claude code regularly asks me questions - I like how anthropic implemented this

Looking at examples I see:

``` c = Sector(radius, start = 180°, end = 270°).translate(y = radius); ```

Programming language that requires (maybe it does not require, but then example is not good) to type degrees. Or maybe it is not designed to be typed and rather ai generated?

They did operate on a "continuous refresh" basis. However, it mostly stopped for almost 2 years now. Other than HW4 I don't think anything else is different between current models and their iterations 2 years ago.

Edit: mostly speaking about Model Y, as Model 3 had actual refresh recently.

Here you go: https://blog.adaptiverisk.com/post/2023-08-22-dataslicer/ Calculations are local, not in the cloud.

shit build quality

That's old news. If build quality is your only concern, I suggest you to check them again. They supposedly improved build quality significantly after initial rollout of M3. As a data point: my family owned and drove 6 different Teslas over last 3 years - we did not have build quality (or any other) issues with any of them. All recent horror stories you heard are because of current Tesla scale and media negative bias against the company - you don't hear similar stories from other manufacturers.

Last two years used Tesla prices were higher than new ones. You need to wait up to a year to get new Tesla though. So you could actually make some money while driving newest versions of cars.

the company optimizes delivery numbers of cars sold by sacrificing quality control

How do you know this? Did you see their internal data? There are lots of anecdotes going around about Tesla's quality. However, with all the TeslaQ it is hard to believe that there is real correlation between anecdotes and data. Here are my anecdotes - I owned 6 Teslas over last several years. Not one of them had any QC issues. I had one service done because I hit tire debris and front break dust shield started making noises. Tesla fixed that for me quickly with no charge. As for the data - during earnings calls they mentioned that they do pay close attention to their customer experience data and they had period of time where service was lagging. But they started addressing this issue and saw improvements. The way they are growing I do believe they need to keep close eye on customer experience, but looks like they understand that themselves and use data to make sure they are on top of this. Unfortunately there's not much reliable independent data to have better understanding of this issue.

Add: The intent of my comment was to ask if parent info is based on specific data or just anecdotes. As an example, I gave my own anecdotes and mentioned that they are not reliable correlation to the data. Somehow the responses I've got are all about anecdotes, mine or others, also some personal judgement of my ability to appreciate cars or judgment of my life circumstances that required me to have these many Teslas. Can we get back to discussing the main point I'm making - do we have data to make any of these judgements?

It does work: NIO does it (they have 700 battery swap stations already). CATL also announced that they will produce swappable car batteries.

I, myself, don't see how this can be more competitive than superchargers. But I do see that some customers would like to have this option.

They did try it in 2013, but abandoned the idea: https://www.tesla.com/videos/battery-swap-event

How Russian people would know about this? You are underestimating efficiency of Russian propaganda machine. Russian government does not shy away from inflicting damage onto Russian people and pointing finger to the West.

Interesting point. How would you resolve this chalantly? 144 million people who probably will struggle to purchase their next iPhone vs 44 million people many of whom might die, loose all property and homes. What is a good way to resolve this in your opinion?

I bet the polls will show overwhelming support - after 8 years of wall to wall Russian propaganda and extermination of opposition most think Putin is their savior from Fascist Ukrainians. (Source: I have relatives who still live there)

I am using a lot of Numpy and Pandas at work and hate them. When I come home I open Mathematica and enjoy every minute of it. It is much more polished, consistent and faster than anything in Python land.

The only place where Python is better if you need to share your code - not everyone has Mathematica license.

Without "the best" the title reads to me as that they somehow removed chunk of original Windows and replaced it with WSL. That's why I came to this topic. I thought to myself - really - so they now replacing windows code with Linux? Original title is clear and not clickbaity.

This is almost 150 years of data. There were regimes with very different macroeconomic conditions (great depression, wars). However I do agree with you that there is a chance that we will see something even more exotic.

For me this type of analysis is always suspicious because it doesn't consider timing. How do I know that when I buy stocks I'm not buying at a peak, or when I need to sell them I'm not going to sell at the bottom. So I ran an analysis [1] where I just used random timing and checked what distribution would be. Turns out if you are long term investor (> 10 years holding period) it is more beneficial to hold stocks than bonds.

"Even if you had to sell your stocks at the bottom of the Great Depression, but held them for more than 20 years before that, you would not suffer a loss in value of your portfolio"

[1] https://www.investingrus.com/blog/safest-bet/

Your point is anecdotal. I actually ran the analysis and found that if you are long term investor - stocks beat bonds hands down. See it here: https://www.investingrus.com/blog/safest-bet/

"Even if you had to sell your stocks at the bottom of the Great Depression, but held them for more than 20 years before that, you would not suffer a loss in value of your portfolio"

We sold both of our gas cars and got Tesla (don’t need two cars right now). We are doing more road trips (1k miles or more) right now than ever. Teslas are awesome on long drives (mainly due to autopilot).

The same article I linked discusses model X that had battery replaced under warranty at more than 300k km. The reason for the replacement was not battery degradation. Here's another article showing graph for up to 200k miles. Looks like Teslas holding capacity quite well even beyond 100k:

https://insideevs.com/news/429818/tesla-model-s-x-battery-ca...

Not everywhere. In Texas most extra renewable capacity is actually at night since at night wind is stronger.

Tesla Model 3 has 100k miles warranty for battery with guarantee that battery will have at least 70% capacity remaining. Actual numbers indicate that degradation usually is significantly less - closer to 90% battery capacity at 100k miles: https://electrek.co/2020/06/06/tesla-battery-degradation-rep...