OpenAI, Adobe, Canva define AI trends as AI chip buying frenzy grows

As we enter the final week of the year, this is perhaps the best time to take stock of how far we’ve come in terms of the technology we connect with. A seminal moment that should set the benchmark for the experience. Gadgets that delivered on their promise and gadgets that didn’t. The journey of fintech has reached the moment when multiple digital payment apps are installed on our mobile phones. But I’ll keep it simple. Given the rapid advancements in AI, you’ve probably interfaced with it in some app without even realizing it. What I want to be careful about is whether this is a good thing or not. I’m not sure whether it’s such a good thing that algorithms lead the way most of the time (please bear with me in many cases). I have already said that the vision of AI is both fascinating and frightening.

Nevertheless, perhaps a summary of everything that happened will serve as a useful reminder for you, as it did for me writing this article in what has felt like a breathless year. Let’s simplify this approach even further (hopefully you like it) and talk about five of the most important AI announcements of the year. As a teaser, next week we’ll ring in the new year by telling you about 10 of the most interesting gadgets that will definitely tempt you to splurge. But my attempt is to explain what point these launches are making. Wider trend lines and generational improvements (wait for that too).

There have been few periods in the past 12 months when OpenAI hasn’t been in the news. Often for unpleasant reasons (cadres including Mira Murati leaving the building). But primarily, their AI models continued to make significant advances. Starting with the GPT-4o model, it includes the ChatGPT search engine, ChatGPT from Apple Intelligence, and the already advanced OpenAI o1 and o1-mini, and o3 LLM. Before leaving OpenAI, Murati promised that AI models in 2025 would have “PhD-level intelligence,” and we’re moving toward that reality at breakneck speed. Maybe.

Few companies are advancing the capabilities of AI while at the same time fully pursuing more secure implementations of that AI. Adobe’s efforts are outstanding. “We’re not building AI models for the sake of it,” Adobe Vice President Deepa Subramaniam said in an interview. At the same time, we have collectively pushed the ecosystem toward the adoption of content credentials to help users identify generations from real media. At the same time, the company’s Firefly model is being rolled out as a standalone generative AI tool, also highlighting its superior Generative Extend for video editing and Adaptive Profile for photo editing, both of which have found their way into Adobe’s apps. I am.

The video generation AI chapter is now well and truly written. OpenAI teased Sora much earlier this year, but it was Adobe that was able to get the Firefly Video model ready for prime time sooner. Meta talked about Movie Gen, an AI video generator, which is also not available to the public. This will only develop in the coming months.

Canva, the unparalleled creative platform, has made bold moves to expand its position around AI, acquisitions, and business, team, and enterprise use cases. Perhaps the plan to increase subscription prices was not well thought out. But that doesn’t take away from the brilliance of Magic Studio’s overhaul, followed by Dream Lab’s generative AI layer (a result of the Leonardo acquisition). Cameron Adams, Canva’s co-founder and chief product officer, said most of the cutting-edge tools in the suite use AI built in-house. We have a lot to look forward to from Canva in the coming years.

At this point, I’d like to remind everyone about a rather unique stance taken by Australian technology company Savage Interactive, makers of the popular Procreate app. They claim that they do not inject any generative AI smarts into these apps. “AI is not our future” and “we will never get there” are strongly worded assertions by CEO James Cuda. He didn’t mince words. “I hate generative AI.” That’s exactly how it feels. Isn’t that what many of us are thinking?

The AI ​​chip war has only just begun. Tech companies are building chips not only for AI companies to train new generative models, but also for consumer devices that run applications and tools built on the same models. Nvidia’s GB200 Grace Blackwell superchip sets the benchmark, but it’s far from a given verdict. Microsoft’s Azure Maia 100 and Cobalt 100 chips, Amazon’s second-generation Trainium, Meta’s MTIA, and Google’s controversial Tensor Processing Unit are examples of momentum building across the industry. On the consumer side, Qualcomm and Apple (the latter for Mac only) are leading the way with AI chips, but AMD is quickly catching up and Intel has no choice but to challenge Intel, which is also facing a current challenge. . The reality is that demand for AI chips is so high that manufacturing can barely keep up. The next frontier could be quantum computing.

Some interesting reading from a bygone era…