Indeed. The current AI salespeople never define their terminology, and this is intentional. If they did, they would instantly lose all funding, the bubble would burst, and they’d need to go find real jobs.
It’s always the same story… Say you have a new amazing “AI thingy” and then when your specific tech looks like it’s vaporware, pivot and point to traditional tech development and claim that there’s substance. Classic bait and switch deflection tactics.
Algorithms and expert machines a weren’t and aren’t AI. Can’t say that I’ve ever played Halo so have no idea about that. This is Lemmy though, so you shouldn’t be surprised that I’ve watched most if Trek, read The Culture and the Asimov robot books.
Your definition is, in fact, wrong. Read the textbooks. Read the dictionaries… But I don’t blame you for having an incorrect definition; that’s what the snake oil salesmen want you to believe.
Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy.
Applications and devices equipped with AI can see and identify objects. They can understand and respond to human language. They can learn from new information and experience. They can make detailed recommendations to users and experts. They can act independently, replacing the need for human intelligence or intervention (a classic example being a self-driving car).
But in 2024, most AI researchers, practitioners and most AI-related headlines are focused on breakthroughs in generative AI (gen AI), a technology that can create original text, images, video and other content. To fully understand generative AI, it’s important to first understand the technologies on which generative AI tools are built: machine learning (ML) and deep learning.
artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since their development in the 1940s, digital computers have been programmed to carry out very complex tasks—such as discovering proofs for mathematical theorems or playing chess—with great proficiency. Despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match full human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in executing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines, voice or handwriting recognition, and chatbots.
Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in engineering, mathematics and computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.[1]
High-profile applications of AI include advanced web search engines, chatbots, virtual assistants, autonomous vehicles, and play and analysis in strategy games (e.g., chess and Go). Since the 2020s, generative AI has become widely available to generate images, audio, and videos from text prompts.
The traditional goals of AI research include learning, reasoning, knowledge representation, planning, natural language processing, and perception, as well as support for robotics.[a] To reach these goals, AI researchers have used techniques including state space search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, operations research, and economics.[b] AI also draws upon psychology, linguistics, philosophy, neuroscience, and other fields.[2] Some companies, such as OpenAI, Google DeepMind and Meta, aim to create artificial general intelligence (AGI) – AI that can complete virtually any cognitive task at least as well as a human.[3]
Artificial intelligence was founded as an academic discipline in 1956,[4] and the field went through multiple cycles of optimism throughout its history,[5][6] followed by periods of disappointment and loss of funding, known as AI winters.[7][8] Funding and interest increased substantially after 2012, when graphics processing units began being used to accelerate neural networks, and deep learning outperformed previous AI techniques.[9] This growth accelerated further after 2017 with the transformer architecture.[10] In the 2020s, an AI boom has coincided with advances in generative AI, which allowed for the creation and modification of media. In addition to AI safety and unintended consequences and harms from the use of AI, ethical concerns, AI’s long-term effects, and potential existential risks have prompted discussions of AI regulation.
Because it’s not real ai. It’s just marketing.
There’s no guarantee, that team AI wouldn’t be even worse.
You play too many video games if you think AI means Cortana. Computer scientists have been building artificial intelligence since the 1950s
Indeed. The current AI salespeople never define their terminology, and this is intentional. If they did, they would instantly lose all funding, the bubble would burst, and they’d need to go find real jobs.
It’s always the same story… Say you have a new amazing “AI thingy” and then when your specific tech looks like it’s vaporware, pivot and point to traditional tech development and claim that there’s substance. Classic bait and switch deflection tactics.
Algorithms and expert machines a weren’t and aren’t AI. Can’t say that I’ve ever played Halo so have no idea about that. This is Lemmy though, so you shouldn’t be surprised that I’ve watched most if Trek, read The Culture and the Asimov robot books.
Expert machines are AI, genetic algorithms are AI, state machines are AI, and the perceptron was AI.
That’s because AI stands for artificial intelligence, and all of those technologies are attempts to artificially produce intelligence.
Your definition is, in fact, wrong. Read the textbooks. Read the dictionaries… But I don’t blame you for having an incorrect definition; that’s what the snake oil salesmen want you to believe.
https://www.ibm.com/think/topics/artificial-intelligence
What is AI?
Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy.
Applications and devices equipped with AI can see and identify objects. They can understand and respond to human language. They can learn from new information and experience. They can make detailed recommendations to users and experts. They can act independently, replacing the need for human intelligence or intervention (a classic example being a self-driving car).
But in 2024, most AI researchers, practitioners and most AI-related headlines are focused on breakthroughs in generative AI (gen AI), a technology that can create original text, images, video and other content. To fully understand generative AI, it’s important to first understand the technologies on which generative AI tools are built: machine learning (ML) and deep learning.
https://www.britannica.com/technology/artificial-intelligence
artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since their development in the 1940s, digital computers have been programmed to carry out very complex tasks—such as discovering proofs for mathematical theorems or playing chess—with great proficiency. Despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match full human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in executing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines, voice or handwriting recognition, and chatbots.
https://en.wikipedia.org/wiki/Artificial_intelligence
Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in engineering, mathematics and computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.[1]
High-profile applications of AI include advanced web search engines, chatbots, virtual assistants, autonomous vehicles, and play and analysis in strategy games (e.g., chess and Go). Since the 2020s, generative AI has become widely available to generate images, audio, and videos from text prompts.
The traditional goals of AI research include learning, reasoning, knowledge representation, planning, natural language processing, and perception, as well as support for robotics.[a] To reach these goals, AI researchers have used techniques including state space search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, operations research, and economics.[b] AI also draws upon psychology, linguistics, philosophy, neuroscience, and other fields.[2] Some companies, such as OpenAI, Google DeepMind and Meta, aim to create artificial general intelligence (AGI) – AI that can complete virtually any cognitive task at least as well as a human.[3]
Artificial intelligence was founded as an academic discipline in 1956,[4] and the field went through multiple cycles of optimism throughout its history,[5][6] followed by periods of disappointment and loss of funding, known as AI winters.[7][8] Funding and interest increased substantially after 2012, when graphics processing units began being used to accelerate neural networks, and deep learning outperformed previous AI techniques.[9] This growth accelerated further after 2017 with the transformer architecture.[10] In the 2020s, an AI boom has coincided with advances in generative AI, which allowed for the creation and modification of media. In addition to AI safety and unintended consequences and harms from the use of AI, ethical concerns, AI’s long-term effects, and potential existential risks have prompted discussions of AI regulation.
You are technically correct.
But non-technical people assume AI to be AGI, which LLMs are not nor ever will be.
That’s because non-technical people watch far more movies than computer science lectures. They think AI is that thing from the movies.
Thanks, gatekeeper! Is margarine real butter? Is saccharine real sugar? Is Lemmy real Internet? Is baseball real sports?
I bet it’s all marketing, all the way down. Nothing is real.
No
No
Yes well part of it
It’s just rounders. A primary school game.