Risks of Large Language Models (LLM)
With all the excitement around chatGPT, it’s easy to lose sight of the unique risks of generative AI. Large language models (LLMs) -- a form of generative AI -- are really good at creating prose that sounds like a native speaker. But because they’re so good at it, large language models may give a false impression they possess actual understanding. They don't! In this video, Phaedra …
Why Large Language Models Hallucinate
Large language models (LLMs) like chatGPT can generate authoritative-sounding prose on many topics and domains, they are also prone to just "make stuff up". Literally plausible sounding nonsense! In this video, Martin Keen explains the different types of "LLMs hallucinations", why they happen, and ends with recommending steps that you, as a LLM user, can take to minimize their occurrence…
The latest AI and Machine Learning tools
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IBM Watson Natural Language Understanding
IBM Watson® Natural Language Understanding uses deep learning to extract meaning and metadata from unstructured text data. Get underneath your data using text analytics to extract categories, classification, entities, keywords, sentiment, emotion, relations and syntax.
AI can help you better serve your customers and cut costs as your staff becomes more productive, and your IT systems and networks become more proactive. Discover new opportunities and gain the full value of your data from diverse sources, faster. Learn how the Watson portfolio for business can boost your AI capabilities and your bottom line.
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The story of Replika, the AI app that becomes you
Replika is a chatbot that creates a digital representation of you. It's strange and fascinating -- but the story behind it is even better.
An AI companion who is eager to learn and would love to see the world through your eyes. Replika is always ready to chat when you need an empathetic friend. Replika was founded by Eugenia Kuyda with the idea to create a personal AI that would help you express and witness yourself by offering a helpful conversation. It’s a space where you can safely share your thoughts, feelings, belief…
How Watson Learns Superhuman Jeopardy! Strategies
Major advances in Question Answering technology were needed for Watson to play Jeopardy! at championship level -- the show requires rapid-fire answers to challenging natural language questions, broad general knowledge, high precision, and accurate confidence estimates. In addition, Jeopardy! features four types of decision making carrying great strategic importance: (1) selecting the nex…
Watson and the Jeopardy! Challenge
See how Watson won Jeopardy! and what it meant for the future of cognitive systems.
AlphaGo – The Movie
With more board configurations than there are atoms in the universe, the ancient Chinese game of Go has long been considered a grand challenge for artificial intelligence. On March 9, 2016, the worlds of Go and artificial intelligence collided in South Korea for an extraordinary best-of-five-game competition, coined The DeepMind Challenge Match. Hundreds of millions of people around the…
AlphaGo is the first computer program to defeat a professional human Go player, the first to defeat a Go world champion, and is arguably the strongest Go player in history.
Google’s Deep Mind Explained! – Self Learning A.I.
For the first time in history we're seeing the successful development and demonstration of general purpose AI... what exactly is DeepMind where did it come from and what can the company's artificial intelligence actually do?
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14 Different Types of Learning in Machine Learning
...there are many different types of learning that you may encounter as a practitioner in the field of machine learning: from whole fields of study to specific techniques.
In this post, you will discover a gentle introduction to the different types of learning that you may encounter in the field of machine learning.
Types of Artificial Intelligence – A detailed guide
We talk about the social, moral and political issues surrounding Artificial Intelligence, Machine Learning and Deep Learning, but often it’s not very clear what these terms mean, how they differ from one another and what might be everyday examples of each. These terms are often used interchangeably despite meaning somewhat different things.
AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the Difference?
These technologies are commonly associated with artificial intelligence, machine learning, deep learning, and neural networks, and while they do all play a role, these terms tend to be used interchangeably in conversation, leading to some confusion around the nuances between them. Hopefully, we can use this blog post to clarify some of the ambiguity here.