Adobe takes home the award thanks to its new, exciting update to Premiere Pro: text-based editing. At NAB, Adobe showed us why Premiere Pro is the go-to editing software for so many editors. While text-based editing was the highlight for us, Adobe also unveiled an impressive range of new features across its Creative Cloud video programs. Adobe showcased new features in Premiere Pro that will be shipping in May. These included text-based editing along with an AI-based workflow powered by Adobe Sensei.

This article is brought to you by Retail Technology Review: Retail Technology Show 2023: Retail Express to join leading tech innovators. Q&A with Ed Betts, Retail Lead Europe at Retail Express, who considers ahead of the show the role of intelligent merchandising technology and its critical place in the future of retail. The critical role that technology plays in retail is unquestionable. Within the industry we are now talking more and more about smart retail technology which is any technology that is used to improve efficiency and effectiveness of operations, such as Artificial Intelligence (AI). So, in short, the Retail Technology Show on 26-27 April in London is where all the leading vendors get together and Retail Express is excited to be there.

German artist Boris Eldagsen seemed to be set for success. His entry won the prize for the creative open category at the Sony World Photography Awards, a prestigious photography competition. The memorable photo shows a black-and-white portrait of two women, possibly mother and daughter, in an eerie, nostalgic, haunting atmosphere. The image was created by an image-generating AI. Eldagsen called it titled PSEUDOMNESIA / The Electrician and submitted it to the competition.

Two months ago, Amazon didn't make a single mention of AI on its earnings call (Google and Microsoft mentioned AI dozens of times each). This past week, by contrast, the company's cloud division, Amazon Web Services (AWS), could talk about little else. As announced by Swami Sivasubramanian, vice president of database, analytics, and machine learning at AWS, the company is all over AI with the launch of new large language models (LLMs) and APIs to access them, as well as CodeWhisperer, a GitHub Copilot competitor, and more. It's not that AWS wasn't working on AI before; Amazon has been working with AI for decades. Rather, it's now impossible to ignore AI.

At first glance, building a large language model (LLM) like GPT-4 into your code might seem simple. The API is a single REST call, taking in text and returning a response based on the input. But in practice things get much more complicated than that. The API is perhaps better thought of as a domain boundary, where you're delivering prompts that define the format the model uses to deliver its output. But that's a critical point: LLMs can be as simple or as complex as you want them to be.

Artificial intelligence's rapid growth has led to advancements like autonomous vehicles, virtual reality, and ChatGPT. But AI technologies and training AI models require a lot of energy, increasing concerns about the environmental impact of AI and its sustainability. To put AI's energy usage into perspective, it took nine days to train one of OpenAI's early model chatbots, MegatronLM. According to TechTarget, during those nine days, 27,648 kilowatt hours of energy was used. That's about the same amount of energy used by three U.S. homes over the course of an entire year.

Mea culpa: I was wrong. The artificial intelligence (AI) singularity is, in fact, here. Whether we like it or not, AI isn't something that will possibly, maybe impact software development in the distant future. No, not every developer is taking advantage of large language models (LLMs) to build or test code. But for those who are, AI is dramatically changing the way they build software.

Low-code and no-code platforms are used to build applications, websites, mobile apps, forms, dashboards, data pipelines, and integrations. No-code platforms help business users, sometimes termed citizen developers, to migrate from spreadsheets, extend beyond email collaborations, and transition from manual task execution to using tools and automations across departments. Low-code platforms are usually for technologists and provide ways to deliver and support software with little or no coding. "You have to remember low code is just a fancy term for abstraction. We are abstracting away non-essential elements in order to simplify the user experience," says Gordon Allott, President and CEO of K3.

Sundar Pichai: This is such an exciting moment because there are a lot of ideas we've had in terms of how we can help our users, but you didn't quite have a powerful technology capability to actually realize those ideas. I think we're moving fast, and when I look at our road map for the next few months, we'll be bringing out a lot of these things like we've done in the last few weeks. Workspace has announced features both in Gmail and Google Docs, which are beginning to roll out. There's a lot more to come. WSJ: What is the key to getting people to move fast on this, and do you still think there is room to move faster? Mr. Pichai: You always want to think about how you can do things as fast as possible. It's important to get it right.

The UK's data regulator has issued a warning to tech companies about protecting personal information when developing and deploying large language, generative AI models. Less than a week after Italy's data privacy regulator banned ChatGPT over alleged privacy violations, the Information Commission's Office (ICO) published a blog post reminding organizations that data protection laws still apply when the personal information being processed comes from publicly accessible sources. "Organisations developing or using generative AI should be considering their data protection obligations from the outset, taking a data protection by design and by default approach," said Stephen Almond, the ICO's director of technology and innovation, in the post. Almond also said that, for organizations processing personal data for the purpose of developing generative AI, there are various questions they should ask themselves, centering on: what their lawful basis for processing personal data is; how they can mitigate security risks; and how they will respond to individual rights requests. "There really can be no excuse for getting the privacy implications of generative AI wrong," Almond said, adding that ChatGPT itself recently told him that "generative AI, like any other technology, has the potential to pose risks to data privacy if not used responsibly."