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Dec 26, 2024 07:20 AM IST
There was scarcely ever a moment in the last 12 months, when OpenAI wasn’t in the headlines.
As we enter the closing week of the year, it’s probably a fitting moment to evaluate the progress we’ve made regarding the technology we engage with. Those pivotal moments which should establish the experiential standards. Devices that fulfilled their promises, and those that fell short. The evolution of fintech has reached a point where multiple digital payment applications are now accessible on our smartphones. However, I’ll keep it straightforward—the swift advancement of AI has likely meant you’ve interacted with it in some application or another, often without your knowledge. The question remains, is this a positive development? I have reservations, particularly about algorithms taking the lead most of the time (often, without your consent). The AI outlook, I’ve previously labeled as “captivating yet alarming”.
Nonetheless, a summary of all that’s occurred may serve as a beneficial reminder for you, just as it would for me to articulate this after what feels like a non-stop year. I’ll streamline the discussion even more (hopefully this will be agreeable to you) and highlight 5 of the most significant AI announcements from the year. Additionally, as a preview, next week we’ll welcome the new year by discussing 10 of the most intriguing devices that have emerged, which have undeniably enticed users to indulge—but the aim is to illustrate where these introductions are leading in terms of broader trends and generational enhancements (please anticipate that too).
- There was scarcely ever a moment in the past 12 months, when OpenAI wasn’t making headlines. Frequently, for disconcerting reasons (executives like Mira Murati departing). But predominantly, for the remarkable advancements their AI models consistently provided. From the GPT-4o model, a ChatGPT search engine, ChatGPT integrated into Apple Intelligence, and they are already looking ahead with OpenAI o1 and o1-mini, as well as the o3 LLMs. Before Murati’s exit from OpenAI, she assured that the 2025 AI models will possess “PhD level intelligence”, and we might be swiftly heading towards that reality.
- Very few corporations, while enhancing the capabilities of their AI, have also advocated for safer implementations of that AI universally. Adobe’s initiatives are notable. “We aren’t creating AI models merely for the sake of it,” Adobe VP Deepa Subramaniam conveyed during an interaction with us. Concurrently, they’ve collectively steered the ecosystem towards accepting content credentials to assist users in identifying generations from genuine media. Moreover, their Firefly model is being utilized as an independent generative AI tool, and also highlights the impressive Generative Extend for video edits and Adaptive Profile for photo edits, both integrated within Adobe’s applications.
- The chapter of video generative AI is now being authentically penned. Even though OpenAI showcased Sora much earlier in the year, it was Adobe that managed to have the Firefly Video model ready for mainstream use sooner. Meta mentioned Movie Gen, their AI video creator, but that’s also currently not accessible to the public. This will evolve in the forthcoming months.
- Canva, an exceptional creative platform, made bold strides with AI, acquisitions, and expanded its positioning to stay relevant for businesses, teams, and enterprise scenarios. Perhaps the decision to raise subscription fees was not as well thought through. Nevertheless, this does not detract from the brilliance of the Magic Studio overhaul succeeded by the Dream Lab generative AI layer, a result of the Leonardo acquisition. Cameron Adams, Canva’s co-founder and Chief Product Officer, expressed that most of the cutting-edge tools in the suite use AI developed in-house. A lot is anticipated from Canva in the forthcoming years.
At this juncture, I must remind everyone of a rather distinct position taken by the Australian tech company Savage Interactive, the creators of the well-known Procreate apps. They assert that they will not embed any generative AI capabilities into these applications. “AI is not our future” and “we’re never going there,” are strong statements from CEO James Cuda. He was blunt in his words: “I really fu**ing hate generative AI,” a precise representation of sentiments. Quite reflective of what many of us are thinking, isn’t it?
The AI chip battles have merely begun. Tech enterprises are designing chips not just for AI companies to train new generative models, but also for consumer gadgets that will operate applications and tools built on those same models. Nvidia’s GB200 Grace Blackwell superchip sets the standard, yet it is far from a definitive conclusion. Microsoft’s Azure Maia 100 and Cobalt 100 chips, Amazon’s second-generation Trainium, Meta’s MTIA, and Google’s controversial Tensor Processing Units exemplify a growing momentum across the industry. On the consumer front, Qualcomm and Apple (the latter specifically for Macs) have taken the lead with AI chips, but AMD is rapidly closing the gap, and Intel in its current predicament has no choice but to keep pace. The truth is, AI chips are in such high demand that manufacturing can barely keep up. The next battleground could indeed be quantum computing.
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