Walnuts. Can’t gorge myself on them, even with them being very healthy they are highly caloric. It helps a small amount is pretty filling though.

It’s got a mount where you can stick a phone or tablet if you want, but nothing built-in.

I’m not sure how that will be road legal in the USA because after the passage of a law in 2018 all vehicles under 10,000 lbs require a backup camera.

“Today’s final rule requires all vehicles under 10,000 pounds, including buses and trucks, manufactured on or after May 1, 2018, to come equipped with rear visibility technology that expands the field of view to enable the driver of a motor vehicle to detect areas behind the vehicle to reduce death and injury resulting from backover incidents. The field of view must include a 10-foot by 20-foot zone directly behind the vehicle. The system must also meet other requirements including image size, linger time, response time, durability, and deactivation.”

source

What ICE car did you buy that fit your desire?

That ford escape hybrid was close too.

What the Escape may have hidden from its cabin interior it amplified in its power train for tech complexity (and cost to repair!). A very common failure on the Escape Hybrid was its ABS/HCU (Anti-Lock Brake System/Hydraulic Control Unit). The cost for this one part is $5500. I suppose that might be fine if it rarely failed, but that wasn’t the case. It failed often and just the cost of that part could economically total the vehicle.

I think you’d do well to take a college communications class. You’d get exposed to diagrams like this that examine and explain what communication is, and how language works to facilitate communication:

She’s fine with a calculator and hard facts. But the “two trains leave on coursetl to pass each other” kind of “make math from description” part that exercises the brain’s ability to select the right equation and use it? Not great.

We’ll be like this, but with building digital things. Our BEST hope is to become the fat and lazy pampered pets of the robots like in WALL-E. The alternative is a little too Matrix for me.

We talk about the “K-shaped economy” where there was an inflection point and our society diverged into two groups: one doing well financially and getting richer and the other continuing to decline financially.

I’m personally seeing separate unrelated K-shaped divergence between one part of our society that continuing to increase in technical knowledge and execution skills and the other falling further away being slaves to digital products designed to separate them from as much of their money as possible.

The first group are avid users of 3D printers and other fabrication techniques. They love a good RESTful API. They’ll chop the back half off of one product and stitch it together with interface electronics and code to the other half of another device just to make their lives slightly better.

The second group will pay $5 for an app that will take Instagram pictures and apply them to some digital in-game item while the app sells their location and personal information to brokers and their car insurance company to jack up their premiums.

So we created multitudes of digital byte-sized monkeys…and gave them m/billions of typewriters. . . :p

You’re not far off from describing primative LLMs. In fact, the recent innovation in the last 5 years was the application of a specific technique published in a paper called “Attention Is All You Need” that the secret sauce is “attention” added via a transformer layer. This concept is what made GPT, Claude, etc the life-like responses they have today.

Kind of like “compressed”. It takes longer/more effort to run them, to produce the same result as a the same model that has not been quantized, where that non-quantized version would consume significantly more RAM but produce the result faster. You would typically only run the quantized model when you’re starved for RAM, which most of us are running LLMs locally.

Think like zipping a file with file compression. It takes less space, but has to be unzipped for you to have usable files again.

“Weights” in LLMs are the “final answer” numbers from the results of model training, and these are the engine of the LLM model. Lets use chocolate chip cookies as an analogy.

The chocolate chip cookies are produced with ingredients, a recipe, labor effort to produce the dough, and then cooking energy/effort to bake chocolate chip cookies. In a traditional AI company, the company gets the ingredients, they write their own recipe, do all the dough creation, and then the energy/labor for baking, and charge you money to get chocolate chip cookies.

An open-weights AI company got all the ingredients, wrote their own recipe, labor effort to produce the dough, and instead of charging you for the dough, you get as much uncooked dough as you want forever. Your only task is to take the dough and cook it yourself and you’ve got free chocolate chip cookies. You can make as many cookies as you want with your own oven. However, you are not given free raw ingredients, nor are your given the recipe to alter it in a way you might like. You can only get the dough for free.

So open-weight AI models (uncooked dough) are LLMs you can use on your own computers (oven) for free and have LLM output ( chocolate chip cookies), but you don’t get the training data (ingredients) nor the training parameters (recipe) that built the open-weight model.

Question, what do you do with it

I use it for both fun throwaway stuff as well as productivity tasks for learning.

Example of fun throwaway:

Do you remember that episode of Seinfeld where the Kramer starts using Facebook marketplace and starts buying the most worthless items before being robbed when trying to get a too-good-to-be-true sale? No? Because it never happened, but you can plug that premise into an crafted LLM prompt and it will pop out a whole TV script with in-character dialog for each actor as well as use of popular existing sets.

Foreign language learning:

I’m studying a foreign language and want to interact with just the level of vocabulary and grammar I have knowledge of right now at my level for practice. I can prompt the LLM to limit itself to just what I know now and adjust the conversation level so I can practice. If I ever get stuck, I can ask the LLM to explain the grammar usage or vocabulary choice.

and how is the data that underlies the model harvested?

I’m not sure what you’re asking here. Are you asking, for example, how the Deepseek model was trained? If so, I answered that above. If not, can you rephrase your question?

The absolutely most generous copyright protection length is in Mexico which is 100 years plus the life of the author when created. So lets generously say a total of 160 years. Most of the rest of the world is 120 year max. Anything outside of that is in the Public Domain. Many things had a much shorter path to the Public Domain falling into it in as little as 20 years.

So lots and lots of stuff is not copyrighted.

As an exercise so I could learn the technology, I trained a model exclusively on the Public Domain works of L Frank Baum, specifically the “Wonderful Wizard of Oz” series (did you know there are 14 books in the series just by Baum?!). The model created is not useful as a tool, and more often than not just produces English gibberish, but every now and then it can produce original coherent statements.

Again, I didn’t do this to produce a useful tool, but rather an exercise to learn how to build models.

They are all trained on copyrighted material without permission, no LLM is ethical

However, this means I can refute your statement because 100% of the input data is public domain novels. Also, I trained it on my own hardware powered 100% by solar power.

I’ve come round to the idea that I will not use LLMs regardless of how “ethically” they can be sourced because their outputs are harmful in a way that builds up, like a very small dose of poison.

How is LLM output any more harmful than output from a human you don’t know? I would agree with you if one were to simply blindly accept anything an LLM gives you as factual. However, I am skeptical of what humans say too. Some are inaccurate out of carelessness, some out of malice. Critical thinking is the key to protection from both errand LLM output and fallible humans.

Additionally, this thread is about locally running LLMs. One of the most dangerous aspects of most large LLMs is the sycophancy where the LLM will try to tell you what you want to hear, even if it needs to creatively invent things that don’t exist or are not true. If you are not aware, running locally means you have all the controls on the model. You’re not subject to whatever settings a large hyperscaler sets up for you. This means, among other things, you can turn down the “temperature” setting, which is the lever that controls how creative an LLM is. Practically what this means is, if you set it to “0” you are allowing it no creative action. If you ask it a question it doesn’t have actual training on, it will tell you effectively “I don’t know” instead of making something up just to have an answer.

It might seem like a romantic or artist’s approach, but with so much spiralling out of our control I’m trying to make the active choice to be more human.

The older I get the more disappointed I get in humanities large group decisions and actions.

Is it really feasible to run it 100% locally?

Yes. My Macbook Air (M2) released in 2022 can run many publicly available LLM models. The ouput is not as fast as using a large powerful datacenter, but for my local needs, I’m not in a hurry. I get about 17 to 30 tokens per second speed running 100% locally.

If yes to the previous: the software doesn’t come from nowhere

For Mac users, the interface comes from here . For the specific LLM models that is a separate question for each.

and ultimately still relies on gas-turbine-powered datacenters

DCs generating power on-site is a relatively new phenomon because existing grids are at capacity, so the only way to bring new DCs online is locally generating power at that DC, usually using gas turbines or even worse, diesel generators. Most if not all of the publicly available models for running on your own hardware were built before those gas-turnbine-generating DCs were a thing.

The public models people are running now have existed for a number of years are likely made on regular utility grid power which is whatever that nation and region uses.

and stolen IP and stolen personal data, no?

The Llama LLM is made by Meta, so probably yes for that one. Deepseek is from an AI research lab in China. QWEN is from Chinese company Alibaba. We don’t know for sure the inputs that created the Chinese models. US AI companies claim a number of the Chinese models are derived from American LLMs, but I haven’t seen (or looked for) proof of these claims.

If what I wrote above is true, what exactly are people arguing when they say it’s still possible to use LLMs ethically

Likely they mean because you don’t have to pay a large LLM owner in a rent-seeking model to run LLMs, nor does a person’s use contribute to further development by those companies.

or true to FOSS philosophy, because … ???

With the open-weight models it doesn’t rely on a commercial license to use, and the interfaces can be truly open source.

His response was ‘just do what you can’. I gave it a couple of months to see anything would come of our conversation but it didn’t.

This sounds like he was okay with you pushing back on any work that was too much and saying “no” to any task beyond your reasonable work limits. Even with this did you feel the damage to the working relationship was just too far gone?

Seems convoluted. Why not just let the business venture fail?

Usually because the business failure could mean thousands of primary job losses, and possible tens of thousands of secondary job losses from other businesses that support the first. Depending on the region, that could have massive ripple effects across the local, regional, and possibly national economy.

We don’t have a strong social safety net in the USA so that would likely lead to large scale poverty, homelessness, and massive increase food insecurity. These things then ripple out to other businesses in the area completely disconnected from the primary failing business causing more job losses as so forth.

The amount of public money to try to support the population and economically revitalize the region is massive when set next to a comparatively small bailout that would maintain the workforce at the primary business and and avoid the other businesses affected secondarily.

In short; its cheaper to pay the bailout so the primary company can pay their bills again than to operate in a pure market economy of boom and bust.

And if the basic function of the business is so integral to the function of society then it should not be a business, but should be a regulated administrered aspect of government.

If a business functioning is so important it needs to get bailed out, in this case it should be nationalized.

This can get messy very quickly:

From a domestic point of view, if the business is one of many providing the product or service, then the government now has a vested interest in driving any public spending to that one nationalized company while the surviving non-nationalized companies attempt to compete.

From an international point of view, if that nationalized company produces products for export, then you get the same problem we have with many companies in trade regulations. For example, the WTO prohibits direct subsidies tied to exports. The USA accuses China of this all the time and is the basis for many import bans in countries around the world.

Could be USA or Italy. What a sad world we live in.

Obviously the workload they were putting on you was way beyond a rational amount for one person. If you’re willing to talk about it, can I ask if you considered simply refusing to do more than “one person’s” amount of work and asked them to prioritize all your tasks so you could work on the things they deemed most important? Obviously this could lead to you being fired, but if you were already set to quit, the outcome would have been the same (except perhaps you’d be eligible for unemployment insurance).

Also i want to someday earn money without having a job

This is possible, but you need to have ownership of something with substantial value that others are willing to give you money for it. Unless you’re given something like this (usually inheriting it) the only way to get one of these is to buy it for a very large sum of money you get from something else that will allow you to earn a small fraction of what you paid for the item of value. So unless you inherent the item, no one starts with this, but its something you can get later in life if you get enough money from elsewhere.

or where i am my own boss

This is possible to do starting with nothing, but its a very hard path. Entrepreneurship pays way WAY less than most hourly jobs for years (possible decades) and you work way WAY harder than any hourly or salary job working for someone else. Finally, the risks to your income are far FAR higher than working for someone else. Failed businesses by entrepreneurs is extremely common, and you’re frequently left with less than nothing because its common to take on debt to start or grow a business. So your business could fail, but your debt doesn’t disappear when your business income disappears.

ive tried the “simple” ways to get a grasp of learning. Ive tried free methods like surveys, games, ebay selling, etc, but i find that those are a waste of time/effort for me atleast and im lucking to break even.

If you’re trying to succeed in areas where anyone can do the thing, you’re competing with everyone that can do that thing. That’s a low chance of succeeding, as you’ve discovered.

The winning move is to specialize. Shrink your competition by doing an activity that you, and a smaller number of people can do.

and i have no talent.

People typically categorize “talent” by specific job roles such as: music, computers, athletics. Instead of a whole career role, identify what individual traits or abilities you have. This is what career counseling is for.

• Are you very detail oriented and can follow a list of instructions perfectly time and time again?
• Do you have good anomaly detection where you can look at a result and realize something is wrong or missing?
• Are there any particular extreme conditions you are quite comfortable working long hours in (high temperature, small spaces, low or no light, etc).
• Do you have extensive cultural understanding of any particular groups (language, customs, traditions)?
• Do you know if you are good working for long periods alone or the opposite where you are constantly with others?
• Do you learn best by reading, hearing, or doing?

These kind of abstract questions, and your answers, can lead you to all kinds of paths that you could be particularly well suited for that others are not! This means you’d be competing with far fewer people for roles that match your specific traits.

In short, do you know yourself well enough yet? If not, seek all kinds of work or experiences that will help you answer questions like this. The most powerful thing for anyone to be successful, in however each of us defines that, is knowing who we each are. Only then do I believe we can each chart our personalized individual paths to success.

So for the average person who won’t get a multi-million dollar loan/inheritance from mommy and daddy

You don’t need a multi-million dollar loan/inheritance to retire with $5 million. You need substantially less and the time for it to compound. A person retiring today with nothing but boring a passive S&P500 investment of $50,000 and 40 years (average working years length) in 1985 would have $5,508,666 right now without ever making another contribution than the first $50k. That’s even going through all the financial downturns during that span of 1987 Black Monday stock market crash, Dotcom bubble burst, 9/11, Great Recession, and COVID.

I’m not disagreeing that most people don’t have $50k when they turn 18 to put into retirement, but I wanted to point out the power of the passive part of this that it only takes $50k with no other action but time to retire with over $5m.