摘要： Customized protein design is now possible because of artificial intelligence (AI), which can be used to address both medicinal and environmental issues. A team at the University of Bayreuth has effectively used a computer-based natural language processing model for protein research under Prof. Dr. Birte Höcker.
摘要： Analog deep learning, a new branch of artificial intelligence, promises quicker processing with less energy use. The amount of time, effort, and money needed to train ever more complex neural network models is soaring as researchers push the limits of machine learning.
摘要： Numerous examples of machine learning show that machine learning (ML) can be extremely useful in a variety of crucial applications, including data mining, natural language processing, picture recognition, and expert systems. In all of these areas and more, ML offers viable solutions, and it is destined to be a cornerstone of our post-apocalyptic civilization.
摘要： With the massive growth of machine learning (ML)-backed services, the term MLops has become a regular part of the conversation — and with good reason.
摘要： In addition to the well-known security challenges faced by devops teams, organizations also need to consider a new source of security challenges: machine learning (ML).
摘要： From NFTs to the metaverse, decentralization is making its way across the creator economy. With the rise of Web3, what lies ahead for creators in 2022?
摘要： Neural architecture search promises to speed up the process of finding neural network architectures that will yield good models for a given dataset.
摘要： Last year, San Francisco-based research lab OpenAI released Codex, an AI model for translating natural language commands into app code. The model, which powers GitHub’s Copilot feature, was heralded at the time as one of the most powerful examples of machine programming, the category of tools that automates the development and maintenance of software. Not to be outdone, DeepMind — the AI lab backed by Google parent company Alphabet — claims to have improved upon Codex in key areas with AlphaCode, a system that can write “competition-level” code.
