Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. This year we will continue to see changes in the tech industry. As we have been preparing for a fundamental in how we work, technology plays a major role in how employees and companies can operate better, smarter, more efficiently and more productively. More than that, tech is a key player in how employees can connect with one another to create a truly collaborative work environment. There are three major areas where we will see a shift across tech.

Hordes of companies are remaking how they do business to stay relevant in a technology-driven world. But hiring great software engineers who can pull off a digital transformation or artificial intelligence project is hard. Enter a growing legion of "citizen developers," empowered by companies like Microsoft, Google, Amazon, Salesforce and ServiceNow. These ordinary business people create apps using software that technology companies call low-code or no-code software development tools. To use these tools, all you need is a web browser.

Machine Learning has wholly integrated into our everyday life. Naturally, many aspiring would-be analysts want to learn the magic behind ML. However, the application of the machine learning process in analyzing data involves a framework of collecting data, creating/choosing a model, preparing, and training the data until predicting the outcome. All of which makes the entire process appear too technical, challenging, and laborious, leaving those who aren't fluent in software development feeling overwhelmed. However, No-code Machine Learning is changing this status quo.

When software providers talk about the technologies they say "democratize" AI, they also talk a lot about "guardrails." That's because the rapidly evolving world of AI tools is still more like a republic governed by the machine-learning elite. Although no-code and low-code AI tools promise to give everyone a chance to build business analytics models or simple applications that use AI to complete tedious tasks, the amateurs whom no-code AI companies refer to as "citizen data scientists" are often required to play with the bumper rails up. That's because toolmakers and management are worried about the risks inherent in allowing just anyone to create sophisticated AI systems. "As you go into low-code and actually more the no-code environment, then there are guardrails as to what you can and can't do," said Ed Abbo, president and chief technology officer at C3 AI, which provides software designed to help people with zero coding experience build machine learning models.

A database used by NFT marketplace OpenSea failed Thursday, which prevented new NFT owners from having their prizes delivered to many of their crypto wallets. The world somehow managed to soldier on despite this disaster, which is both kind of funny and illustrative of how hard it will be to build truly decentralized tech infrastructure. MetaMask is a crypto wallet that stores NFTs, and it relies on OpenSea's API to let it know when one of its users has purchased a new NFT. However, as reported by Vice, that API went down Thursday morning and remains down as of this afternoon, which threw a wrench into Twitter's announcement that NFTs were now available for purchase as avatars. Whatever your take on the wacky world of Web3, decentralized tech infrastructure is an interesting opportunity that a lot of smart people and deep-pocketed companies are working to advance.

Artificial intelligence and machine learning today allow us to reduce the time demanded for solving a certain problem from months and years to minutes. For example, it took your grandma years of practice to learn the right temperature for growing her zucchinis. If she had AI, she would do it much faster. But the problem is that even today not so many people can program ― only 0,5%! This is where no-code platforms step into the game.

By 2024, as much as 65% of application development will be done on no-code/low-code platforms, according to a Gartner Magic Quadrant report. The no-code application platforms have shown a lot of promise and productivity gains. Such platforms help organisations to automate and digitise processes with cloud-based mobile apps. Below, we have curated the top 12 no-code machine learning platforms in 2021. About: BigML is an open-source no-code tool that provides commoditised machine learning as a service for business analysts and application integration.

Microsoft today announced the public preview of its Power Virtual Agents tool, a new no-code tool for building chatbots that's part of the company's Power Platform, which also includes Microsoft Flow automation tool, which is being renamed to Power Automate today, and Power BI. Built on top of Azure's existing AI smarts and tools for building bots, Power Virtual Agents promises to make building a chatbot almost as easy as writing a Word document. With this, anybody within an organization could build a bot that walks a new employee through the onboarding experience for example. "Power virtual agent is the newest addition to the Power Platform family," said Microsoft's Charles Lamanna in an interview ahead of today's announcement. "Power Virtual Agent is very much focused on the same type of low code, accessible to anybody, no matter whether they're a business user or business analyst or professional developer, to go build a conversational agent that's AI-driven and can actually solve problems for your employees, for your customers, for your partners, in a very natural way." Power Virtual Agents handles the full lifecycle of the bot building experience, from the creation of the dialog to making it available in chat systems that include Teams, Slack, Facebook Messenger and others.