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Capital One AI chief sees path to explainable AI

ZDNet

The so-called black box of artificial intelligence has been a topic of much debate in recent years. Can neural networks whose functioning includes "hidden layers" that defy easy explanation ever be trusted with the most sensitive tasks society might ask of them? One practitioner offers an adamant "yes," insisting older approaches to statistics and probability are not necessarily more transparent than today's deep learning. Nitzan Mekel-Bobrov a year ago joined McLean, Va.-based Capital One Financial as its artificial intelligence chief. At $36 billion in market capitalization, Capital One is dwarfed by retail banking competitors such as JP Morgan Chase and Bank of America, but the firm takes pride in its use of technology throughout its operations, and Mekel-Bobrov explained in an hour-long interview with ZDNet how machine learning is proliferating throughout parts of the organization.


What OpenAI and GitHub's "AI pair programmer" means for the software industry

#artificialintelligence

OpenAI has once again made the headlines, this time with Copilot, an AI-powered programming tool jointly built with GitHub. Built on top of GPT-3, OpenAI's famous language model, Copilot is an autocomplete tool that provides relevant (and sometimes lengthy) suggestions as you write code. Copilot is currently available to select applicants as an extension in Visual Studio Code, the flagship programming tool of Microsoft, GitHub's parent company. While the AI-powered code generator is still a work in progress, it provides some interesting hints about the business of large language models and the future directions of the software industry. The official website of Copilot describes it as an "AI pair programmer" that suggests "whole lines or entire functions right inside your editor."


Will AI coding assistants like GitHub's Copilot transform developers' jobs?

#artificialintelligence

OpenAI has once again made the headlines, this time with Copilot, an AI-powered programming tool jointly built with GitHub. Built on top of GPT-3, OpenAI's famous language model, Copilot is an autocomplete tool that provides relevant (and sometimes lengthy) suggestions as you write code. Copilot is currently available to select applicants as an extension in Visual Studio Code, the flagship programming tool of Microsoft, GitHub's parent company. While the AI-powered code generator is still a work in progress, it provides some interesting hints about the business of large language models and the future directions of the software industry. Attend the tech festival of the year and get your super early bird ticket now!


Can artificial intelligence make software development more productive?

#artificialintelligence

The idea that software can be developed by artificial intelligence without requiring a human developer opens a world of possibilities -- and questions. Software development AI applications are targeted mainly at developers, promising to act as'co-pilots', and making them more productive. Could this be taken even further to the point where developers are not required at all? What benefit could it have for business users? Having recently been granted preview access to the OpenAI Codex application, Ravi Sawhney took it on a tour through the lens of a business user.


Bugged: The Ugly Side Of No Code AI Platforms

#artificialintelligence

"What is'best practice' at the time of writing may slowly become'bad practice' as the cybersecurity landscape evolves." Modern-day deep learning (DL) models, especially the ones powering sophisticated NLP based applications, have become so advanced that they can even run code diagnostics and perform interventions on a codebase. For example, GitHub recently released Copilot, an AI-based programming assistant that can generate code in popular programming languages. All one has to do is give some context to the Copilot, such as comments, function names, and surrounding code. Copilot is built on OpenAI's GPT-3 that is trained on open-source code, including "public code…with insecure coding patterns", thus giving rise to the potential for "synthesise[d] code that contains these undesirable patterns".