Why Machine Intelligence is NOT Artificial [Human] Intelligence? AI is NOT Machine Learning, ML is NOT AHI, and Artificial NNs are NOT Human NNs. AA/AI rule 2: All Artificial Intelligence is Artificial Human Intelligence (AHI), divided as Narrow AI, Artificial General Intelligence (AGI), or Artificial Superintelligence (ASI). AA/AI rule 3: Real Machine Intelligence (MI) is NOT Artificial Human Intelligence (AHI), the capability of a computer system to mimic human intelligence/cognitive functions/behavior such as perception, learning, reasoning and problem-solving or NL communication. AA/AI rule 4: Machine Learning is NOT AHI.

Article: OpenAI invites everyone to test new AI-powered chatbot--with amusing results - Ars Technica Chatbot: ChatGPT Chatbot - Open AI Open AI, one of the leading Artificial Intelligence organizations, has released an AI Chatbot. Called ChatGPT, it can talk about many technical subjects. But, since it is trained on a vast amount of data gathered from the Internet, it can do other things, like talk about movies. Here is what I got when I asked for a movie script involving pirates: Read the article above to learn more about the chatbot! You can try the chatbot yourself with the second link. An Open AI account is required, but it's free.

Diabetes is a chronic condition characterized by high blood glucose levels due to insulin resistance or insufficient insulin production. Around 463 million people worldwide have a diabetes diagnosis; 95% of these people have type 2 diabetes. If untreated, type 2 diabetes can damage the heart, eyes, kidneys, and nerves. Prediabetes, or "intermediate hyperglycemia," is the high risk stage before type 2 diabetes when blood sugar levels are above average but below the threshold for diabetes. Around 7.3% of the global adult population have prediabetes, and over 80% of adults in the United States with the condition are unaware they have it.

Despite recent advances in RL research, the ability to generalize to new tasks remains one of the major issues in both reinforcement learning (RL) and decision-making. RL agents perform remarkably in a single-task setting but frequently make mistakes when faced with unforeseen obstacles. Additionally, single-task RL agents can largely overfit the tasks they are trained on, rendering them unsuitable for real-world applications. This is where a general agent that can successfully handle various unprecedented tasks and unforeseen difficulties can be useful. The vast majority of general agents are trained using a variety of diverse tasks.

The study was groundbreaking, not only for the deep-learning predictability, but also because it allowed researchers to see what the model learned about the immune system. "DeepTCR's predictive power is exciting," said Dr. John-William Sidhom, first author of the study, "but what I found more fascinating is that we were able to view what the model learned about the immune system's response to immunotherapy." He also mentioned the great potential for creating future medications with the information. "We can now exploit that information to develop more robust models, and possibly better treatment approaches, for many diseases, even those outside of oncology." DeepTCR was developed by Dr. Sidhom while he was an M.D./Ph.D student at the Johns Hopkins University School of Medicine.

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Presented by Alex John London, Clara L. West Professor of Ethics and Philosophy and director, Center for Ethics and Policy, Carnegie Mellon University. He has also served as an expert ethics consultant with national and international organizations, including the National Institutes of Health, the World Health Organization, and the World Medical Association, and the World Bank. Supported by the Department of Human Genetics and the Year of Data & Society., powered by Localist Event Calendar Software

OpenAI has released ChatGPT, a new dialogue language model (LM) based on the GPT-3.5 family series (trained on text and code) and similar to InstructGPT (aligned with reinforcement learning through human feedback). The company set up an online demo and people are losing their minds over it. In a nutshell, ChatGPT is a chatbot that can "answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests." This nicely encapsulates the reason why ChatGPT is so special: "admit", "challenge", and "reject" are unusual verbs to describe the behavior of an LM. However, it isn't an exaggeration in ChatGPT's case (countless examples that I'll share soon assert it).

Though Chapter Three was "Fortnite's" shortest chapter, it brought many big changes to the gameplay. It added sliding, mantling and a faster movement speed, letting players get around the map in new ways. Season Two briefly removed building -- the mechanic that sets "Fortnite" apart from its battle royale competitors -- from the main game; it later returned as its own game mode. The no build mode lets players eliminate each other without the pressure to gather materials, but also without the ability to create their own cover when they come under fire. The latest season let players phase through chromed walls and transform into fast-moving chrome blobs to surprise enemies. And as ever, we saw crossover characters from universes like Star Wars and Marvel, continuing "Fortnite's" transformation into a franchise-filled metaverse.

ChatGPT, a newly released application from OpenAI, is giving users amazing answers to questions, and many of them are amazingly wrong. Open AI hasn't released a full new model since GPT-3 came out in June of 2020, and that model was only released in full to the public about a year ago. The company is expected to release its next model, GPT-4, later this year or early next year. But as a sort of surprise, OpenAI somewhat quietly released a user-friendly and astonishingly lucid GPT-3-based chatbot called ChatGPT earlier this week. ChatGPT answers prompts in a human-adjacent, straightforward way.