1x Tsla Discussion Threads

[hosede] 27/4/2024 18:35

Simon
That article if correct suggests Robotaxis are dead in the water

[hosede] 27/4/2024 18:26

They've all got it in for Tesla

[simon gordon] 27/4/2024 18:11

Medium - 25/4/24:

AI Is Hitting A Hard Ceiling It Can’t Pass

Is it the end of AI’s rampant development?

by Will Lockett

There has been an insane amount of hype surrounding AI over the past few months. Supposedly, Teslas are going to entirely drive themselves in a year or two, AI will be smarter than humans next year, and an army of a billion AI-powered robots will replace human workers by 2040, and that is just the AI promises made by Elon Musk so far this year. The entire AI industry is awash with predictions and promises like this, and it feels like AI development is on an unstoppable exponential trajectory we humans simply can’t stop. However, that is far from the truth. You see, AI is starting to hit a development ceiling of diminishing returns, rendering these extravagant promises utterly hollow. Let me explain.

To understand this problem, we need to understand the basic principles of how AI works. Modern AIs use deep learning algorithms and artificial neural networks to find trends in data. They can then extrapolate from this data or generate new data along the same trend line. This starts by “training” the AI, where a massive amount of data is fed into it for analysis, enabling it to find these trends. After this, the AI can be queried for an output. This basic concept powers computer vision, self-driving cars, chatbots and generative AI. This is a somewhat reductive explanation, but it is all we need to understand for now.

Over the past few years, AIs have become significantly more capable. This has been partly due to better programming and algorithm development. But it is also 90% thanks to the fact that AIs have been trained on significantly larger datasets. This allows them to more accurately understand the trends in the data and, therefore, more accurately generate results. But there is a problem; we are seeing drastically diminishing returns in AI training, both in terms of data and computational power needed.

Let’s start with the data. Let’s say we built a simple computer vision AI designed to recognise dogs and cats, and we trained it using images and videos of 100 dogs and cats, and it can correctly identify them 60% of the time. If we doubled the number of training images and videos to 200, its recognition rate would improve, but only marginally to something like 65%. If we doubled the training images and videos again to 400, its improvement would be even more marginal, to something like 67.5%.

This is partly because when you have a smaller data set, each new training image gives you proportionally more new data to work with than adding a new training image to a larger dataset. However, it is also because AI can quickly make novel connections and trends in a small dataset, as it only has to find a trend that works with a few examples. But as that dataset grows, finding new and novel trends and connections that work for the entire dataset becomes harder and harder. These new trends and connections from larger datasets enable an AI to get better and more capable. As such, we are seeing the amount of training data required to improve an AI by a set amount increase dramatically as we reach a point of diminishing returns with AI training.

But there is another problem. AI training is incredibly computationally hungry. The AI has to compare each individual point of data to every other data point in the set to find these connections and trends. This means that for each bit of data you add to an AI training database, the amount of computational work it takes to train that AI on that database increases exponentially. As such, even if you can acquire the vast amount of data it takes to train these ever-improving AIs, the amount of physical computing power and energy it requires will eventually grow to the point of impossibility.

Sadly, there is evidence that we are at a stage where both the diminishing returns of training dataset growth and the exponential increase in computing power required to use said datasets are enforcing a hard ceiling on AI development.

Take OpenAI’s flagship AI ChatGPT4. Its improvement over ChatGPT3 was smaller than ChatGPT3’s improvement over ChatGPT2, and even though it was more accurate, it still had the same problems of hallucinating facts and lack of understanding as ChatGPT3 did. Now, OpenAI is very tight-lipped on how it develops its AIs, but experts have investigated and found that ChatGPT3 used a training dataset about 78 times larger than ChatGPT2, and ChatGPT4 uses a dataset 571 times larger than ChatGPT3! Yet, despite this considerable up tick in the training dataset size, ChatGPT4 still has significant flaws that significantly limit its use cases. For example, It can’t be trusted to write anything remotely fact-based, as it still makes up facts.

Some estimates put ChatGPT4’s raw training dataset at 45 TB of plaintext. This means that for the next iteration to be as big of an improvement as ChatGPT4 was over ChatGPT3, the training dataset would need to be tens of thousands of TBs. Acquiring and preparing that amount of plaintext data, even with OpenAI’s dubious methods, is simply impractical. However, actually using this dataset to train their AI could use so much energy that the cost renders the AI entirely unviable, even for a non-profit.

That isn’t hyperbole. OpenAI CEO Sam Altman has gone on record saying that an energy breakthrough, like nuclear fusion, is needed to make advanced AI viable. Sadly, even if we do unlock nuclear fusion, it isn’t likely to be cheaper than our current energy this century or possibly even next century. In fact, no form of energy is set to become significantly cheaper than anything we currently have. So, this proposed solution to AI’s energy problem is deeply misleading.

This viewpoint is supported by some very serious studies. One from the University of Massachusetts Amherst looked at the computation and energy costs associated with improving an image recognition AI performance to over 95% accuracy. They found that training such a model would cost $100 billion and produce as much carbon emissions as New York City does in a month. Bearing in mind that this is for an AI that still gets it catastrophically wrong 5% of the time. The study also highlighted that increasing accuracy to 99% would take exponentially more cost and carbon emissions.

This is why Tesla will never develop full self-driving cars with its current approach. Their Autopilot and FSD can only sense the world around them through this type of AI computer vision, and for FSD to become fully self-driving, its image recognition accuracy needs to be approaching 100% accuracy. As this study shows, it could take far more money than even Tesla has to get their AI that good.

In other words, unless the AI industry can find a way to be more efficient with its AI training and its computational load, it won’t be able to break past this limit, and AI development will completely stagnate. Now, possible solutions are on the horizon, such as far more efficient AI hardware incorporating analogue and quantum technologies and new AI architectures that requires significantly smaller training datasets. However, these concepts are still in their infancy and are potentially decades away from being used in the real world.

In short, be prepared for AI to massively fall short of expectations over the next few years.

[dominiccummings] 27/4/2024 10:55

Good pick Johnwise, but you won't give my 4wd Model 3 a race will you!

[johnwise] 26/4/2024 17:06

Trying to rig the market with tax penalties on petrol or incentives on electric will never be enough to persuade the majority of people to purchase EVs, they are expensive, no second hand value, inconvenient if drive reasonable miles and not environmentally friendly since require rare metals to build, can’t recycle the batteries and majority of charging is from carbon produced electricity.

My mode of transport, four wheel drive diesel, It's Fantastic

[hosede] 26/4/2024 16:39

I think the notion that Tesla is going to make $2.64 this year is highly optimistic. 45 cents in Q1 and things look to be getting worse. A significant annual loss looks a distinct possibility

[simon gordon] 26/4/2024 16:34

H,


The AI/Robotics idea is what Musk is selling to the market. From the same article:

Tesla’s first-quarter earnings could have been an extreme disappointment to the bulls who just last week, let alone last year, were expecting a much better outcome. True to form, however, CEO Elon Musk used the conference call to talk about anything except their automotive business.

"I think Cathie Wood said it best. Like really, we should be thought of as an AI or robotics company. If you value Tesla as just like an auto company [then] fundamentally, it’s just the wrong framework and if you ask the wrong question, then the right answer is impossible."

And:

"The way to think of Tesla is almost entirely in terms of solving autonomy and being able to turn on that autonomy for a gigantic fleet. And I think it might be the biggest asset value appreciation in history when that day happens, when you can do unsupervised full self-driving."

Who wants to miss out on the biggest asset value appreciation in history? Not the Tesla Illuminati, who responded jubilantly. At one point on Wednesday morning the stock was up 16 per cent, or more than $80bn in market cap. That’s more than a whole Diageo, or Richemont, or Glencore. It’s also more than an entire Volkswagen, or Stellantis, or Ferrari.

[johnwise] 26/4/2024 16:27

Four Candles

All that tax payers money spent on the Torys New Green Wind Mill Deal, To make energy unaffordable..

Wind producing 1.5 percent

Live generation data from the Great Britain electricity grid

[hpcg] 26/4/2024 16:26

Musk is going independent with AI. Irrespective, the short thesis on Tesla is entirely based on revenue, margin, and prospective return multiples. That's it, the end.

Careful - I'm afraid you don't understand black body radiation and the Stafan-Boltzmann law. If the outer reaches of the atmosphere is insulated from the earth it cools, and if it cools it radiates less heat. The radiation the earth is hit with by the sun remains the same, so the earth's lower atmosphere heats up. The suns rays are much higher frequency than those of the re-emitted radiation, before you ask, again physics.

[hosede] 26/4/2024 13:49

Careful
You are, I'm afraid rather out of date. The problem now is much less CO2 and much more water vapour (ca 3 x worse) about which we can do very little. As the temperature rises, the amount of it in the atmosphere increases (7% for every degree C)

[cfb2] 26/4/2024 13:41

blusteradjuster: Happens when traders think they can make a quick buck from shorting Tesla. I'm not engaging with them because they just post links to incorrect or badly researched video, no facts, no reputable sources and many strange opinions.

For example:
We remember the Professor from Imperial, a statistical expert saying that without a lockdown Covid deaths would rise to 250,000 over the next few weeks.
No dynamic analysis at all, as if we would not modify our behaviour without compulsion after we see many of our neighbours and friends dying.

We now live in an age of idiot experts, the term Dr or Professor has been devalued.

Anyone with the opinion that Doctors and Professors, with a minimum of peer reviewed post grad work, should be ignored in preference to someone who has fallen off the turnip truck tells me they will not have the critical thinking skills necessary to engage in a coherent argument.

[careful] 26/4/2024 12:17

Climate scientists and their extrapolated theories.

We remember the Professor from Imperial, a statistical expert saying that without a lockdown Covid deaths would rise to 250,000 over the next few weeks.
No dynamic analysis at all, as if we would not modify our behaviour without compulsion after we see many of our neighbours and friends dying.

We now live in an age of idiot experts, the term Dr or Professor has been devalued.

What cars have to do with climate change we all wonder about.
A simple plot af the measurements of the levels of Co2 various distances from motorways is revealing.
After about 200 meters it barely exists. Heath issues, well yes that is obvious. Often a popular way of suicide was to shut a garage door and leave the engine running.

But global warming, I think not, CO2 will not easy drift up to 30,000 feet where the temperature is minus 40 deg.
Coal fired power stations, well yes, now you are talking turkey. Way back there were chimney sweeps, the chimneys of every house were filled with the most disgusting soot, filthy.
The Chinese and Indians are still building coal fired power stations at a pace. They argue that per capita, with their huge populations, they are much cleaner than America.
They will need those power station to charge their electric vehicles.
Discuss...Electric vehicles are dirtier than small petrol cars. Number required.

[hosede] 26/4/2024 11:56

I guess Cathy bought most of them!

[johnwise] 26/4/2024 10:46

Monster insider trading alert: Former Tesla executive sells $180 million of TSLA shares

Although criticism is growing regarding the ethics and fairness of individuals trading stocks of companies in which they have extensive insider information, such a practice continues, with one of the recent examples including a former Tesla (NASDAQ: TSLA) top engineering executive.

Specifically, Andrew Baglino, who resigned from his position as the senior vice president of powertrain and energy engineering at Tesla a couple of weeks ago, has sold over 1.1 million TSLA shares worth about $181.4 million, according to the information shared by markets analyst Barchart in an X post on April 26.

[hosede] 26/4/2024 10:37

Some climate scientist group estimated that the cost of global warming would be over $30Trn a year by 2050 - not that far in the future!
It's difficult to translate that rather nebulous fgure into reality, but I think it means that overall standards of living will be massively reduced.
Food energy and shelter will be paramount for most people, and private cars (of any type) are likely to be rareties.

Whatever! - the idea that life will be like today but we will all be charging around in EVs is a fantasy

[simon gordon] 25/4/2024 09:55

FT - 25/4/24:

Hours after Musk’s call with investors, BYD, Tesla’s largest rival, announced that it planned to bring its ultra-cheap Seagull EV to Europe and the UK from next year.

The vehicle, which sells for less than $10,000 in China, has caused near-panic among western carmakers, who argue they simply cannot compete with such prices.

...“China has built an industry that can produce excellent cars at truly remarkable price points almost all through the range of products,” said James Anderson, a managing partner at Lingotto Investment Management, which holds Tesla shares. “A sub-$10,000 BYD Seagull domestically is a clarion call.”

He told the FT that Tesla “is acknowledging the reality of the challenge of Chinese pricing”.

The Model 2 — or whatever version of a cheaper car takes its place in the line-up — accounts for about half of analysts’ projections for Tesla’s long-term sales.

If the plans had been shelved or pared back in ambition, Tesla — which once aimed to grow to the size of Toyota and Volkswagen combined by 2030 — would for now remain a more modest manufacturer than expected.

The idea that the company would kill the model “doesn’t make any sense”, said one former executive, noting that Musk used to “school” those around him on the ever-urgent need to reduce costs.

“The whole premise of the gigafactory, the whole point of getting the [battery] pack price down, was to get cheaper cars,” the former executive added. “If he really wants mass adoption, he must know from the turmoil of the last year that affordability is the big issue”.

[hosede] 24/4/2024 22:40

More problems - I'm afraid Tesla will get blamed for everything. If it had been a "normal" car, the make would probably not even have been mentioned.

[blusteradjuster] 24/4/2024 16:10

Don’t be too gloomy about Tesla and its EV rivals.

[simon gordon] 24/4/2024 12:08

Nissan going all in on solid-state batteries:

FT - 24/4/24:

Last week, in the shell of a factory that Nissan insists will be churning out solid-state batteries by 2028, an executive of the Japanese carmaker fired back at scepticism about the nascent technology from companies he says are clinging to the past.

“All the battery suppliers want to keep enjoying the liquid-type batteries, which they have now. They’ve already made a big investment so not only CATL, but all the battery suppliers are not so very positive on solid state yet,” said the executive on the sidelines of a tour.

He was responding to claims made recently by the founder and chief executive of CATL, the Chinese company that dominates the electric vehicle battery industry, that the much-hyped solid-state batteries did not work well enough, lacked durability and still had safety problems.

It is not a criticism that Japan’s carmakers take lightly. Toyota led the way on research into solid-state batteries — which avoid the need for liquid electrolyte used in today’s technology and promise more range and better safety for electric vehicles — and they could be the deus ex machina that transforms Japanese carmakers’ growth prospects.

That is why investors and legacy battery makers, are watching, hawk-like, for signs that Japanese companies can make good on claims they will be able to commercialise the tech in the coming years. Toyota is aiming for as early as 2027, Nissan the year after and Honda by the end of the decade.

[blusteradjuster] 24/4/2024 10:49

It has been a long-time since anyway suggested TSLA might be 'going to 0'.

I'm so old I remember some, otherwise respectable, posters suggesting things like 'TSLA is a fraud' and 'they're going to zero' many moons ago..

[mauricemonkey] 24/4/2024 10:11

OOoooffff - that free cash flow miss.
Meant to be $650m, actually -$2.5bn.
Tesla likely structurally loss making, sales falling and prices collapsing. Could be the beginning of the end.

[johnwise] 24/4/2024 06:53

Tesla announces Q1 financial results; revenue slumps amid operational challenges

Tesla unveiled its first-quarter earnings on Tuesday after market close.