Google’s Chatbot AI Can Code
Google’s AI-powered internet search chatbot, Bard, can now help generate and debug code in over 20 different programming languages. Users can instruct Bard to solve programming tasks and request explanations of code snippets in C++, Go, Java, JavaScript, Python, and TypeScript. Bard can also generate useful functions for the analysis of Google Sheets data. However, users should be careful as Bard is still in the early stages of development and may sometimes provide inaccurate, misleading, or incomplete information. According to Paige Bailer, Group Product Manager at Google Research, “Bard may give you working code that doesn’t produce the expected output, or provide you with code that is not optimal or incomplete.”
Google believes that Bard’s new capabilities have the potential to offer new ways of writing code, creating test cases, and updating APIs for developers. However, for beginner programmers, it may be more difficult to verify Bard’s output for accuracy. It is not clear if these tools are always worth using as it can take more time and effort to understand and correct their code than developers writing it themselves.
Era of Giant AI Models is Over, Says OpenAI CEO
Sam Altman, the CEO of OpenAI, has stated that making neural networks bigger may not be the way forward to advancing AI capabilities. Although models with more parameters lead to better performance, Altman believes that scaling systems could become increasingly expensive to train and the improvements may not be worth the effort. OpenAI is now looking at other ways to improve neural networks, such as using reinforcement learning with human feedback for ChatGPT, which guides the model to generate more human-like text.
It is still early days for AI, and new breakthroughs in machine learning, neural network architecture, and hardware will continue to emerge, leading to further evolution in the industry.
Microsoft Developing Custom AI Chip
Microsoft has reportedly started designing its custom AI processor, codenamed Athena, to provide the computational resources required for OpenAI to develop and deploy its technologies. The company has invested $10 billion into OpenAI and has signed a deal to license the startup’s technology exclusively. Microsoft’s search chatbot, Bing, which uses OpenAI’s GPT-4 to power its internet search results, can benefit from the new chip, which can train and run AI models.
By building its silicon chip, Microsoft can optimize the design to support OpenAI’s technology, its cloud customers, and its own AI-powered products. The company could also save money if it doesn’t have to rely as much on third-party hardware vendors, such as Nvidia. OpenAI employees have been assisting Microsoft in testing Athena.
Generative AI and Healthcare
Microsoft and Epic, the makers of electronic health record-keeping software adopted by thousands of hospitals in the US, will collaborate to apply generative AI technology to improve healthcare. Developers will build new AI features using Microsoft tools that will run on the Azure OpenAI Service over Epic’s software.
The GPT-4 will provide the project with relevant data using Epic’s self-service reporting tool, SlicerDicer, enabling clinicians to extract useful data, including reducing costs and finding answers to questions locally and at a broader level. Institutions such as UC San Diego Health, UW Health in Madison, Wisconsin, and Stanford Health Care have already deployed software that drafts automated responses using Microsoft’s resources. Epic and Microsoft believe that generative AI can help healthcare organizations function more productively and efficiently.
Editor Notes
Bard, Bing, and Athena are the latest AI innovations developed by Google and Microsoft, designed to improve programming and search functions, and offer more efficient healthcare. As OpenAI looks for other methods to improve neural networks, Microsoft’s ambitious bet on a custom chip could potentially enhance the company’s AI-based products while also supporting OpenAI’s technological advancements.
Microsoft’s foray into generative AI in healthcare in partnership with Epic demonstrates the potential for AI-powered implementations in the healthcare industry. As the industry continues to advance, we can expect many significant developments that leverage AI to improve disease diagnosis, drug discovery, and even patient outcomes.
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