You do realize that every posted on the Fediverse is open and publicly available? It’s not locked behind some API or controlled by any one company or entity.
Fediverse is the Wikipedia of encyclopedias and any researcher or engineer, including myself, can and will use Lemmy data to create AI datasets with absolutely no restrictions.
To add to this insight, there are many recent publications showing the dramatic improvements of adding another modality like vision to language models.
While this is my conjecture that is loosely supported by existing research, I personally believe that multimodality is the secret to understanding human intelligence.
I am an LLM researcher at MIT, and hopefully this will help.
As others have answered, LLMs have only learned the ability to autocomplete given some input, known as the prompt. Functionally, the model is strictly predicting the probability of the next word+, called tokens, with some randomness injected so the output isn’t exactly the same for any given prompt.
The probability of the next word comes from what was in the model’s training data, in combination with a very complex mathematical method to compute the impact of all previous words with every other previous word and with the new predicted word, called self-attention, but you can think of this like a computed relatedness factor.
This relatedness factor is very computationally expensive and grows exponentially, so models are limited by how many previous words can be used to compute relatedness. This limitation is called the Context Window. The recent breakthroughs in LLMs come from the use of very large context windows to learn the relationships of as many words as possible.
This process of predicting the next word is repeated iteratively until a special stop token is generated, which tells the model go stop generating more words. So literally, the models builds entire responses one word at a time from left to right.
Because all future words are predicated on the previously stated words in either the prompt or subsequent generated words, it becomes impossible to apply even the most basic logical concepts, unless all the components required are present in the prompt or have somehow serendipitously been stated by the model in its generated response.
This is also why LLMs tend to work better when you ask them to work out all the steps of a problem instead of jumping to a conclusion, and why the best models tend to rely on extremely verbose answers to give you the simple piece of information you were looking for.
From this fundamental understanding, hopefully you can now reason the LLM limitations in factual understanding as well. For instance, if a given fact was never mentioned in the training data, or an answer simply doesn’t exist, the model will make it up, inferring the next most likely word to create a plausible sounding statement. Essentially, the model has been faking language understanding so much, that even when the model has no factual basis for an answer, it can easily trick a unwitting human into believing the answer to be correct.
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+more specifically these words are tokens which usually contain some smaller part of a word. For instance, understand and able would be represented as two tokens that when put together would become the word understandable.
Agreed.
Nevertheless, the Federal regulators will have an uphill battle as mentioned in the article.
Neither “puffery” nor “corporate optimism” counts as fraud, according to US courts, and the DOJ would need to prove that Tesla knew its claims were untrue.
The big thing they could get Tesla on is the safety record for autosteer. But again there would need to be proof it was known.
I am a pilot and this is NOT how autopilot works.
There is some autoland capabilities in the larger commercial airliners, but autopilot can be as simple as a wing-leveler.
The waypoints must be programmed by the pilot in the GPS. Altitude is entirely controlled by the pilot, not the plane, except when on a programming instrument approach, and only when it captures the glideslope (so you need to be in the correct general area in 3d space for it to work).
An autopilot is actually a major hazard to the untrained pilot and has killed many, many untrained pilots as a result.
Whereas when I get in my Tesla, I use voice commands to say where I want to go and now-a-days, I don’t have to make interventions. Even when it was first released 6 years ago, it still did more than most aircraft autopilots.
“If it wasn’t hard, it wouldn’t be worth doing”
I’m convinced that we should use the same requirements to fly an airplane as driving a car.
As a pilot, there are several items I need to log on regular intervals to remain proficient so that I can continue to fly with passengersor fly under certain conditions. The biggest one being the need for a Flight Review every two years.
If we did the bare minimum and implemented a Driving Review every two years, our roads would be a lot safer, and a lot less people would die. If people cared as much about driving deaths as they did flying deaths, the world would be a much better place.
The victims have beed identified as the owner of the flight school, a flight instructor, and a student.
https://www.wtnh.com/new-england-news/no-survivors-after-plane-crash-in-greenfield/
It’s literally an area chart. There’s no way to “skew” it in this format. $800B of $6,300B in spending is always going to be 12.6% no matter how you slice it.
You are looking at two different tax systems. The effective US tax rate (the rate you actually pay is much much less). Our household makes $300k per year, and we have a $650k net worth. Our income taxes every year? Less than 7% of that, which is absurdly low. The ultra wealthy are taxed even less than that. The US is propped up by taxes from the middle-class because the more you makes, the easier it becomes to optimize and lower your effective tax rate. We need to tax the rich more.
The actual study claims that top 10% is $41k and accounts for 50% of carbon emissions. No where does it normalize incomes for those from Kenya as the article claims. So these incomes are viewed globally. If you are in the US and make more than $20/hr hours a week, you are top 10%.
$67/hr makes you top 1%.
Others are calling to eat the rich without realizing that the global rich includes low wage earners flipping burgers at McDonald’s (I’m in Boston and minimum wage is $15/hr and an assistant manager can be hired for $22/hr).
https://oxfamilibrary.openrepository.com/bitstream/10546/621551/2/cr-climate-equality-201123-en.pdf
I’m an AI researcher at one of the world’s top universities on the topic. While you are correct that no AI has demonstrated self-agency, it doesn’t mean that it won’t imitate such actions.
These days, when people think AI, they mostly are referring to Language Models as these are what most people will interact with. A language model is trained on a corpus of documents. In the event of Large Language Models like ChatGPT, they are trained on just about any written document in existence. This includes Hollywood scripts and short stories concerning sentient AI.
If put in the right starting conditions by a user, any language model will start to behave as if it were sentient, imitating the training data from its corpus. This could have serious consequences if not protected against.
I am a satellite software engineer turned program manager. This is not unexpected in this current environment, however the conditions that created the environment are abnormal.
This solar cycle is much stronger than past cycles. I’m on mobile, so I can’t get a good screenshot, but you can go here to see this cycle and the last cycle, as well as an overlay of a normal cycle https://www.swpc.noaa.gov/products/solar-cycle-progression
As solar flux increases, the atmosphere expands considerably, causing more drag than predicted. During periods of solar minimum, satellites can remain in a very low orbit with minimal station keeping. However, at normal levels of solar maximum, 5 year orbits can easily degrade to 1 year orbits. Forecasters says we are still a year away from solar maximum, and flux is already higher than last cycle’s all time high (which was also an anomalously strong cycle). So it will get worse before it gets better.
TLDR: Satellites are falling out of the sky because the sun is angy
I wholeheartedly agree with the purpose of this community and what it advocates for, but I wanted to add some rebuttals to your points.
You mention you have the privilege of not using your car. In car centric parts of the world, which is anything that isn’t a big city, this is a privilege. My family that lives in a town of 50,000 people in Germany still need to use their cars every day! There is only a bus system to get them around. Each working age adult uses their car every day! Including the one who lives in Köln and literally walks across the street to his office because car transportation is far more time efficient than transit.
See anecdote above. I live in Boston, which is supposedly extremely transit friendly and the T and commuter rail, while remarkably extensive, are abysmal. I rode it for two months until I finally gave up and got a car. I live in a house 0.5 miles from the commuter rail station and it’s the cheapest around at $750k, I should be able to have reliable transport to MIT/Kendall.
Your issues with driving, being honked at, being annoyed with lack of right of way, all seem to come from inexperience driving in the city. On roads with speed limits of 30 mph, there is no right of way, it’s just about whoever goes first. After some time, you learn what to expect from locals and adapt to their style. But I understand if driving in a big city makes people uncomfortable. There is a lot going on, and a lot to pay attention to.
Schedule. My god is our transit schedule awful. Commuter rail only once every hour. It’s either 5 minutes early or 20 minutes late regularly. So it’s completely unreliable. The Red line is now slow as fuck. Crawling at 10 mph in most areas now. It’s faster to ride your bike between stations, and get stopped by every traffic light than it is to ride the train. And now the red line only has service every 20-30 minutes!
I loved visiting London. We even got a rental to see things like Stonehenge or Brighton, but I never felt the need to use the car much within the city. While I thoroughly enjoyed driving through parts of London like tiny bridges that had inches of clearance on either side of the vehicle, or massive roundabouts near Victoria station, I never needed to do that for local journeys.
It takes 30 minutes for me to drive to work, but 50-90 minutes to go by public transit and I literally live in a massive transit corridor with service from my house directly to work. It’s absolutely absurd. Essentially, transit only broadly works in US if you live in NYC. It’s too sparse in SF to be used widely. Too sparse in DC. Chicago is 10 times worse with it’s urban sprawl. And unreliable as fuck in Boston. Boston doesn’t even have a reasonable train to the goddamned airport (yes I know about the blue line, but it’s still a 15 min bus from the blue line station, and you can only transfer to the blue line from the green line).
This is why people drive. Because for the vast majority off us, even those in Europe, there is no better alternative. If transit was so much cheaper, then why doesn’t every village of 10,000 people in Europe have a tram? There are simply too many places people want to go, and only extreme density can make transit cost effective.
The same argument could be said for an apartment building too. We need to collectively realize that Single Family Houses are a luxury that most of us will never see in our lifetimes. Our grandparents were able to enjoy them at low prices because the US had half the population it does today.
Restrictive building codes that only permit building SFH is the cause of our housing shortage and not short term rentals that consist of 0.2%-1% of all dwellings.
Many leading economist argue for land value tax only as a way to incentivize the most efficient use for our most valuable resource. If land tax was used instead of property tax, a multi-acre plot in a dense urban would be taxed just as much a multi-story apartment building that takes up the same amount of space.
See the Strongtowns article on the subject. https://www.strongtowns.org/journal/2019/3/8/if-the-land-tax-is-such-a-good-idea-why-isnt-it-being-implemented
At it’s core, this is the root cause of the housing crisis. We do not have enough supply. The amount of Airbnb’s that exist is extremely miniscule and the targeting of Airbnbs is an intentional distraction tactic.
Depending on the source, 1% to 0.2% of all dwellings are listed for short-term rental in the US. That’s crazy small and has very little impact on housing prices overall.
The fact of the matter is that Single Family Homes are an incredible luxury that our parents and grandparents were able to enjoy when the country had half as many people as it does now. It is no longer sustainable to expect a SFH in the US, and the American public continuing to cling to that dream and restrictive zoning practices are really what is driving up prices.
If you want an affordable house you will need to move to a rural area where land and labor are cheap. If you want to live near any reasonably sized city, you better be upper middle class to even think about buying a SFH.
We used to run an Airbnb out of the spare rooms in our house. It was very cheaply priced, and we were always booked out for months. Super host status and everything. It was clear most people just look at the price and never the description or rules. We rented two bedrooms with a shared bathroom, and the amount of complaints we received because they had to share a bathroom with someone else was obnoxious.
We closed up shop during the pandemic and just used those rooms as guest rooms instead. In hindsight it wasn’t worth the hassle of dealing with self-centered people who expect an experience superior to that hotels at a quarter the price. We also had some fantastic guests that we loved having stay with us, but the few bad experiences dramatically overshadowed all the good decent people.
Airbnb’s are so shitty today because their customers are just as equally shitty on aggregate.
Cab prices tend to be more consistent across all times of day and location. In Boston an Uber 10 miles west from the airport can cost upwards of $120 depending on the time. A cab would be $60.
The same Uber to the airport is typically much cheaper always at $40.
Someone did the math and realized we would need a 130% tariff on all goods to replace current income tax revenue.
People’s number one concern is inflation. If that tariff is created we will see 100% inflation over night!