This is a most excellent place for technology news and articles.
Medical use is absolutely revolutionary. From GP's consultations to reading tests results, radios, AI is already better than humans and will be getting better and better.
Computers are exceptionally good at storing large amount of data, and with ML they are great at taking a lot of input and inferring a result from that. This is essentially diagnosing in a nutshell.
I pasted your question verbatim into Bing Chat. Here's what it responded with:
Artificial Intelligence (AI) indeed has a wide range of benefits that extend beyond the ones you’ve mentioned. Here are some areas where AI is making a significant impact:
- Healthcare: AI is used in predicting disease outbreaks, drug discovery, personalized treatment plans, and improving patient care. For example, machine learning models can analyze medical images to detect diseases at early stages.
- Education: AI can provide personalized learning experiences, identify gaps in learning materials, and automate administrative tasks. It can adapt to individual learning styles, making education more accessible.
- Environment: AI can help in climate modeling, predicting natural disasters, and monitoring wildlife. It’s also used in optimizing energy usage in buildings and manufacturing processes, contributing to sustainability.
- Transportation: Autonomous vehicles use AI for navigation, safety, and traffic management. AI can also optimize logistics, leading to reduced costs and environmental impact.
- Security: AI can enhance cybersecurity by detecting unusual patterns or anomalies in data, helping to prevent cyber attacks. It’s also used in surveillance systems to identify potential threats.
- Accessibility: AI can help people with disabilities by providing tools that improve their ability to interact with the world. Examples include speech recognition for those unable to use a keyboard, and visual recognition systems that can describe the environment to visually impaired individuals.
While it’s true that AI can be used to generate profits for corporations, it’s important to remember that many of these advancements also lead to societal benefits. However, like any technology, AI can be misused, and it’s crucial to have regulations and ethical guidelines in place to prevent such misuse. The creation of “bots and fake content” you mentioned is one such misuse, and efforts are ongoing to combat these issues.
In conclusion, AI has the potential to greatly benefit society in many ways, but it’s equally important to be aware of and address its challenges.
Seems like a pretty comprehensive list of the things I'm aware of myself. There's also tons of interesting future applications being worked on that, if they pan out, will be hugely beneficial in all sorts of ways. From what I've seen of what the tech is capable of we're looking at a revolution here.
No one knows the long term benefits/costs yet, but its potentially more empowering to small creators than large ones. Everyone has access to the same tools, and for instance, if it can offload a bunch of work from an indy game dev, that could let them focus more on the part of the game design process they are most skilled at/interested in.
Everyone has access to the same tools
go make me something with Sora to see what kind of equal access you think you have
It's massively important in the sciences, both for computing purposes and theoretical design and investigation purposes.
AI is completely revolutionizing genetics research and subjects like biochemistry and pharmacology, because it's able to extrapolate from already identified genes and compounds and find new ones or identify the purposes of genes just from their sequence structure.
It's made processes that would take weeks or months just to identify a single new component to something that takes days or hours.
There are lots of things that are very hard to program, but people can do very easily. For example, play Go or recognize that an animal is a bird.
Machine learning/ai makes it competitively simple to make computers do some of these things, but at the cost of efficiency and speed at runtime. This is true if computers vs people as well, a human brain is much slower, less efficient, and less accurate than a calculator.
Machine learning/AI is exciting because it enables computers to quickly be trained to do tasks that were impossible or would have required years of dedicated effort. The tech world is excited about it because whole new enterprises and areas of tech may spring up, big markets that were previously out of reach.
Downsides:
AI uses a lot more electricity. Especially for things that computers can already do, using AI is very inefficient.
Limited control. You train an ai model to do a task, but you don't have direct control over how it thinks. If chatgpt gives a wrong answer, they can't just trace the program and figure out why. It takes serious effort to figure out how chatgpt answers simple questions, so figuring out how it gets complex answers or why an answer is wrong is nearly impossible at this point. This also applies to unwanted behaviors,if you had a really good history chatbot who happened to turn out racist, you can't just turn that off. You end up having to retrain the model, or secretly add "make sure your answer isn't racist" to every submitted prompt.
I would've found it extremely useful in school for studying advanced topics in biology, and now I use it to explain programming concepts to me, or to explain other languages. Some of the answers really do feel like you have a world-class tutor right next to you. It's not without errors but it's mostly accurate and insightful.
It's also really good at helping you search for things that you can't just type into a search box using keywords. Like, you can give it a general description of what you're thinking about and it'll guess. I've used it for TV shows from the 90-00s I largely forgot about, but also words, phrases, or concepts I can't quite remember. One time I was trying to remember a famous experiment but gave it the wrong scientist and it correctly guessed who it was and what the experiment was about.
It's also useful for brainstorming. You give it a general description of what you're doing and it'll give you somewhat generic recommendations of what you could expect other people to do so that you cover most bases. I've also used this for discussions where I'm not sure about my position so I'll ask it to get a better idea about the problem and to figure out what I'm not considering.
Overall, I think it's a great general purpose assistant.
I think as a tool to synthesize and collect and organize information to help people make decisions, it has potential. Much like how machine learning is used to look at a bunch of MRI scans and highlight abnormalities and then medical professional looks at those anomalies to decide if they might be a tumor. But a machine is really good at finding things that are anomalous enough to be worth looking at. 
Things that you might have delegated to a secretary or assistant or business analyst might be worthwhile done by an LLM. “sort all these papers by which ones understood the topic the best so I can read those first“ “Do any of these articles contain new information I haven’t seen before?“ “based on the Billboard top 20, create 5 catchy beats for a backing track” “Draft a letter to this customer apologizing for our error and offering them a coupon for their next order” “analyze this email I wrote and help me make the tone more professional” 
I am terrified by what is going to be possible with phishing scams, spam email, fake articles, deep fake videos, reproduction of copyrighted works, an overwhelming volume of trademarks and patents that are meaningless, obtuse contracts that are purposely difficult for a human to read but contain surreptitious loopholes, software that is full of flaws and back doors, and corporations putting more barriers between customers and customer service people.
“find me the 50 most popular articles on this topic, synthesize them all into a 20 bullet point summary and highlight for me the differences of opinion presented so I can understand both sides of the issue” - super useful
“Generate 100,000 unique variations on a very professional email correspondence from a Nigerian Prince offering to pay $50,000 transaction fee for assistance with an international wire transfer “ - no
Unfortunately I don’t think there are any incentives for the companies building these things to limit use or install the guard rails necessary. And our laws, which always run a little behind technology, are thoroughly outpaced by the rate of innovation here. The very old people in charge of governments have no chance of staying ahead of these companies. It will get much worse before it ever gets better.
Honestly, we should just stick to porn. The Internet should just be for porn because everything else we do with it seems to turn evil. 🫤
Lots of boring applications that are beneficial in focused use cases.
Computer vision is great for optical character recognition, think scanning documents to digitize them, depositing checks from your phone, etc. Also some good computer vision use cases for scanning plants to see what they are, facial recognition for labeling the photos in your phone etc…
Also some decent opportunities in medical research with protein analysis for development of medicine, and (again) computer vision to detect cancerous cells, read X-rays and MRIs.
Today all the hype is about generative AI with content creation which is enabled with Transformer technology, but it’s basically just version 2 (or maybe more) of Recurrent Neural Networks, or RNNs. Back in 2015 I remember this essay, The Unreasonable Effectiveness of RNNs being just as novel and exciting as ChatGPT.
We’re still burdened with this comment from the first paragraph, though.
Within a few dozen minutes of training my first baby model (with rather arbitrarily-chosen hyperparameters) started to generate very nice looking descriptions of images that were on the edge of making sense.
This will likely be a very difficult chasm to cross, because there is a lot more to human knowledge than thinking of the next letter in a word or the next word in a sentence. We have knowledge domains where, as an individual we may be brilliant, and others where we may be ignorant. Generative AI is trying to become a genius in all areas at once, and finds itself borrowing “knowledge” from Shakespearean literature to answer questions about modern philosophy because the order of the words in the sentences is roughly similar given a noun it used 200 words ago.
Enter Tiny Language Models. Using the technology from large language models, but hyper focused to write children’s stories appears to have progress with specialization, and could allow generative AI to stay focused and stop sounding incoherent when the details matter.
This is relatively full circle in my opinion, RNNs were designed to solve one problem well, then they unexpectedly generalized well, and the hunt was on for the premier generalized model. That hunt advanced the technology by enormous amounts, and now that technology is being used in Tiny Models, which is again looking to solve specific use cases extraordinarily well.
Still very TBD to see what use cases can be identified that add value, but recent advancements to seem ripe to transition gen AI from a novelty to something truly game changing.
AI is a very broad topic. Unless you only want to talk about Large Language Models (like ChatGPT) or AI Image Generators (Midjourney) there are a lot of uses for AI that you seem to not be considering.
It's great for upscaling old videos: (this would fall under image generating AI since it can be used for colorizing, improving details, and adding in additional frames) so that you end up with something like: https://www.youtube.com/watch?v=hZ1OgQL9_Cw
It's useful for scanning an image for text and being able to copy it out (OCR).
It's excellent if you're deaf, or sitting in a lobby with a muted live broadcast and want to see what is being said with closed captions (Speech to Text).
Flying your own drone with object detection/avoidance.
There's a lot more, but basically, it's great at taking mundane tasks where you're stuck doing the same (or similar) thing over, and over, and over again, and automating it.
Here is an alternative Piped link(s):
https://www.piped.video/watch?v=hZ1OgQL9_Cw
Piped is a privacy-respecting open-source alternative frontend to YouTube.
I'm open-source; check me out at GitHub.
If by AI you mean current language learning models then it looks like it can do some useful stuff and is worrying how close it is to doing amazing things.
If by AI you mean a more general concept of artificial intelligence then yeah. Intelligence iis one of the most important resources for getting what we want. This is not to say there are not valid concerns with AI but the potential is crazy, like humans not needing to work levels.
Most email spam detection and antimalware use ML. There are use cases in medicine with trying to predict whether someone has a condition early
It's also being used in drug R&D to find similar compounds like antimicrobial activity, afaik.
Machine learning is important in healthcare and it's going to get better and better. If you train an algorithm on two sets of data where one is a collection of normal scans and the other from patients with an abnormality, it's often more accurate than a medical professional in sorting new scans.
As for the fancy chatbot side of things, I suspect it's only going to lead to a bunch of middle management dickheads believing they can lay off staff until the inevitable happens and it blows up in their faces.
Not for you or I.
AI has some interesting use cases, but should not be trusted 100%.
Like github copilot ( or any "code copilot"):
Like translations ( code or language ):
Like classification of text/Images for moderation:
But dont do anything that is IMPORTANT with AI, only use it for fun or if you know if the code/text the AI wrote is correct!
Adding to the language section, it's also really good at guessing words if you give it a decent definition. I think this has other applications but it's quite useful for people like me with the occasionally leaky brain.
I have sometimes the same issue!
The legal industry is going to get turned on its head when AI can read, comment, and write contracts.
A 2023 study by researchers at Princeton University, the University of Pennsylvania and New York University found that “legal services” is among the industries most exposed to occupational change from generative AI.
https://arxiv.org/pdf/2303.01157.pdf
Another report, published in 2023 by economists at Goldman Sachs, estimated that 44 percent of legal work could be automated by emerging AI tools.
Much like automated machinery, it could in theory free the workers to do more important, valuable work and leave the menial stuff for the machine/AI. In theory this should make everyone richer as the companies can produce stuff cheaper and so more of the profits can go to worker salaries.
Unfortunately what happens is that the extra productivity doesn't go to the workers, but just let's the owners of the companies take more of the money with fewer expenses. Usually rather firing the human worker rather than giving them a more useful position.
So yea I'm not sure myself tbh
No no you found the actual "use" for AI as far as businesses go. They don't care about the human cost of adopting AI and firing large swaths of workers just profits.
Which is why governments should be quickly moving to highly regulate AI and it's uses. But governments are slow plodding things full of old people who get confused with toasters.
As always capitalism kills.
