AI language models like LaMDA and GPT-3 produce fascinating results that are often indistinguishable from human-written texts and conversations. Yes – you could ask whether or not these models are sentient, but I suggest we focus on building use cases for these new capabilities and look for ways to prevent misuse → More
Sam is probably very different to the chatbots you have seen before. She can have natural conversations, understand and respond to questions – and she has an opinion on everything. She has read the entire Wikipedia, knows all books in existence, and she can provide detailed explanations on any topic you ask her about. If she is in the mood for it, that is! → More
AI in the current business landscape
Many companies and organizations are working on AI initiatives and come with the best of intentions. But often these efforts are isolated, with little thought given to how they might fit into a larger ecosystem. This can lead to friction, duplication of effort, wasted resources and a general lack of coordination. Additionally, it is normal for companies to be motivated primarily by profit, which can lead to sub-optimal solutions or even ethical concerns.
In contrast, the open source model of development – as exemplified by projects like Wikipedia – is based on collaboration and the sharing of knowledge. This model has proven to be highly effective, and we believe it can be applied to the development of AI solutions. By working together, we can pool resources, ideas and expertise to create solutions that are greater than the sum of their parts. This is the model that Electric Minds is based on, and we invite you to join us in building a better future.
How you can get involved
This initiative is at an early stage, and we are looking for companies and organizations who are interested in collaborating on AI projects that have a positive impact on society. If you are working on an AI project that you think could benefit from our approach, please get in touch. We are also looking for individuals with expertise in AI, machine learning or data science who are interested in contributing to our efforts.
Our goal is not to build yet another app or platform, but rather to facilitate conversations and connect people with the resources they need to drive innovation. If you are working on something that you think could benefit from our approach, or if you would like to get involved in our work, we would love to hear from you.
What is AI, exactly? And what is the difference between AI and Machine Learning?
In short, artificial intelligence is about teaching computers to do things that normally require human intelligence, like solving problems, gaining insights, and making connections based on understanding and intuition. This can be done through a number of methods, including process automation, machine learning, and data analytics. Google Search is one example of an AI application – the system knows what you are looking for based on your past search history, provides you with relevant results, and keeps learning from your interactions to get better over time.
AI is not a new concept – it has been around for centuries in various forms, although the term “artificial intelligence” was only coined in the 1950s, and its definition has been evolving ever since. Modern AI is used in many different ways, from chatbots and digital voice assistants to self-driving cars and predictive maintenance.
Machine learning is a subset of AI that deals with the ability of machines to learn from data and improve their performance over time without being explicitly programmed. Machine learning algorithms are able to automatically improve given more data, using neural networks that mimic the way the human brain learns. While this sounds like a science fiction concept, it is actually already being used in many everyday applications, such as email filtering, computer vision, and fraud detection. Have you recently noticed that your social media feeds seem to show you more of what you want to see? That’s machine learning at work!
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