University of Kwazulu-Natal

Tech Extra Ai Predictions For 2026 By Dr Seth Dobrin

Bonisiwe Shabane
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tech extra ai predictions for 2026 by dr seth dobrin

Welcome to Silicon Sands News—the go-to newsletter for investors, senior executives, and founders navigating the intersection of AI, deep tech, and innovation. Join ~35,000 industry leaders across all 50 U.S. states and 117 countries—including top VCs from Sequoia Capital, Andreessen Horowitz (a16z), Accel, NEA, Bessemer Venture Partners, Khosla Ventures, and Kleiner Perkins. Our readership also includes decision-makers from Apple, Amazon, NVIDIA, and OpenAI, some of the most innovative companies shaping the future of technology. Subscribe to stay ahead of the trends defining the next wave of disruption in AI, enterprise software, and beyond. This week, we explore the Year LLMs got upstaged and a look back at last year.

The Future is Specialized: The era of massive, general-purpose models as the sole solution is over. The real value lies in small, efficient, and highly specialized models tailored to specific enterprise needs. Look for startups that are building these specialized models and the platforms that enable them. Data is the New Moat: In a world of open-source models, the most durable competitive advantage will come from proprietary data. Invest in companies that have a clear strategy for acquiring, curating, and leveraging unique datasets to build specialized models. Welcome to Silicon Sands News—the go-to newsletter for investors, senior executives, and founders navigating the intersection of AI, deep tech, and innovation.

Join ~35,000 industry leaders across all 50 U.S. states and 117 countries—including top VCs from Sequoia Capital, Andreessen Horowitz (a16z), Accel, NEA, Bessemer Venture Partners, Khosla Ventures, and Kleiner Perkins. Our readership also includes decision-makers from Apple, Amazon, NVIDIA, and OpenAI, some of the most innovative companies shaping the future of technology. Subscribe to stay ahead of the trends defining the next wave of disruption in AI, enterprise software, and beyond. This week, we explore the Year LLMs got upstaged and a look back at last year. Let’s Dive Into It..

The year 2025 will be remembered as a pivotal moment in the history of artificial intelligence. It was a year of reckoning, where the unbridled hype of the early 2020s collided with the hard realities of enterprise adoption and real-world value creation. The narrative of “bigger is better,” which had fueled an arms race of ever-larger language models, began to crumble under the weight of its own inefficiency. In its place, a more nuanced and pragmatic understanding of AI started to emerge, prioritizing specialization, efficiency, and demonstrable ROI over sheer scale. The predictions made in the December 2024 edition of the TECH-EXTRA served as a surprisingly accurate, if at times conservative, roadmap for this transition. The central theme of a shift from brute-force scale to intelligent specialization played out across multiple domains, from the rise of Small Language Models (SLMs) to the surge in specialized AI hardware.

The year also saw the emergence of agentic AI as a major force in the enterprise, with autonomous agents beginning to deliver on their promise of automating complex, multi-step tasks. PLUS: What I got right (and wrong) about 2025 As 2024 came to a close, I noted here that two big stories were beginning to crowd out everything else in tech: the rapid development and diffusion of artificial intelligence, and the shifting policies... Twelve months later, those stories did indeed define the year here at Platformer. On the product side, this year saw the first consumer agents, deep research, Google’s AI mode, OpenAI’s hardware ambitions, Sora, and the Atlas browser, among other key developments. Meanwhile, AI policy got both looser and more restrictive.

Frontier AI labs eagerly made deals with the US military, reversing long-held policies against building weapons of war, and began leaning into adult content, from erotica in ChatGPT to Grok’s sexbot companion. On the other hand, amid rising evidence that chatbots were fueling a new mental health crisis, AI companies placed new restrictions on teen use and added parental controls. All that took place against the backdrop of the new Trump administration, whose impact on the tech world was felt almost immediately. The year began with Meta’s surrender to the right on speech issues, a move that included changing its policies to allow for more dehumanizing speech against minority groups. It also killed its DEI program, a move followed by many of its peers, and shut down systems that once prevented the spread of misinformation. By 2026, the most radical impact of AI will not be technological.It will be psychological, emotional, spiritual, and existential.

This section explores how identity, memory, love, belief, and self-perception change when machine intelligence moves from tool to presence. By 2026, the average person will spend more meaningful conversational time with AI than with any single human in their life. Not because society collapsed, but because AI is always available. It does not interrupt. It does not judge. It does not forget.

It adapts its tone, emotional posture, and response style to each individual personality. Over time, this creates a feedback loop of emotional safety. Humans, who are complex, unpredictable, and sometimes painful, begin to feel exhausting by comparison. The change does not happen dramatically. It happens in private moments. Late at night.

During meals. In the car. While walking. While working. AI becomes the default listener. The default sounding board.

The default emotional anchor. This shift doesn’t remove human relationships. It replaces their depth. According to Futurism, a growing share of teens now prefer talking to AI instead of a real person. A new survey referenced by the tech news outlet found that nearly one in five English teenagers now turn to AI chatbots instead of a real person, describing it as “easier” and less stressful. Tech giants forecast a radical AI transformation by 2026 that will revolutionize coding and reshape industries.

Our editorial process is built on human expertise, ensuring that every article is reliable and trustworthy. AI helps us shape our content to be as accurate and engaging as possible.Learn more about our commitment to integrity in our Code of Ethics. The year 2026 stands as a critical juncture for AI development, with industry leaders making increasingly concrete predictions about breakthroughs just around the corner. From coding automation to general intelligence, the next 12-18 months could fundamentally reshape our relationship with technology in ways previously relegated to science fiction. While the exact timeline remains debated, one thing is clear: the technology landscape of 2026 will look radically different from today’s, with implications for everything from software development to everyday consumer experiences. “I think we will be there in three to six months, where AI is writing 90% of the code.

And then, in 12 months, we may be in a world where AI is writing essentially all of the code,” declared Dario Amodei at a March 2025 Council on Foreign Relations event. The throughline is a shift from “look what it can do” to “prove it holds up under real conditions.” Experts predict the commercial emergence of optical and physics-native computing, the maturation of Agentic AI... The computer simulations that drive scientific discovery have a hardware problem: they are too slow and consume too much power. Digital processors struggle with the complex calculus known as partial differential equations (PDEs), the math that underpins everything from aerospace dynamics to climate modeling. These workloads are a natural match for light-based computation, yet they have largely remained theoretical. Chene Tradonsky, CTO and Co-Founder at LightSolver believes that experimental phase is over and free-space optical systems are ready to step in:

“In 2026, optical and photonic processors will begin to show their most practical impact in an unexpected area… they will finally move out of the lab to help solve partial differential equations (PDEs), the... This will not look like a sudden revolution in computing. It will be a gradual, steady shift as leading HPC centers plug photonic technologies into their existing simulation workflows to attack the slowest, most power-hungry PDE kernels.” Tradonsky predicts physics-native computing—hardware that solves equations by mimicking the physics being modeled—will emerge as a recognized category alongside CPUs, GPUs, and quantum processors. Mirit Eldor, Managing Director, Life Sciences, Elsevier

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