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Last year we experienced rapid advancement in AI and 2025 will be coined by even more ground-breaking innovation. As we kick off the year, I’ve made a list of nine trends I’m watching. They fit into four broad themes: 1) The power challenges facing datacenters; 2) The rise of THE Agentic era and the shift to inference; 3) The rise of open-weight models; 4) Advances in memory and how that will accelerate AI.
Here’s a clickable list of all nine:
Theme 1: AI’s Power Problems
1) Datacenters Go Dark
2) Efficiency Is On The Board Agenda
Theme 2: Agentic AI and Inference
3) Inference Takes the Lead
4) Agentic AI Unleashed
5) The GPU Will Face Its First Real Challenge
Theme 3: Open-Weight Models Rise
6) Open Models Rule
7) Sovereign AI Goes Global
Theme 4: Big Advances in Memory
8) Memory Optimization Drives AI Forward
9) Energy Efficiency Redefines AI Hardware
Theme 1
AI’s Power Problems
1) Datacenters Go Dark
Racks will sit empty as power shortages begin to hit hard. Expect operators who rely on GPUs to relocate near power stations or even build their own power plants to keep up with the AI surge. By the end of the year, the conversation around deploying AI at scale will be dominated by struggles to adapt to power shortages and the need for higher degrees of power efficiency. New innovations will help, but governments and utilities around the world will come under pressure to fast-track power grid improvements.
We’ve already seen a preview of this as Nvidia’s Blackwell chips have posed huge deployment challenges. Few datacenters can support chips with Blackwell’s power density.
2) Efficiency Is On the Board Agenda
As this power crunch unfolds, enterprise leaders will face pressure from their boards to deploy AI efficiently, balancing ROI requirements with rising power costs as well as carbon emissions goals.
Theme 2
Agentic AI and Inference
3) Inference Takes the Lead
This will be the year that Inference will overtake training AI models as the dominant AI workload. As real-time AI applications go mainstream, cloud and data center workloads will shift decisively to inference, largely thanks to the growth of Agentic AI.
4) Agentic AI Unleashed
AI agents will become autonomous. And thanks to recent 10x speed boosts in LLMs and specialized hardware, we can expect AI agents that can plan, reason, and remain aware of real-time information. Agents will use many kinds of input to execute complex, multi-step projects on your behalf and with minimal need for your intervention.
5) The GPU Will Face Its First Real Challenge
The shift to inference and the rise of Agentic AI will lead to a leveling of the playing field. Alternative hardware solutions will rise, and the GPU’s dominance in the AI hardware stack will show some vulnerabilities as more power-efficient competitors that are also better-suited for inference will redefine the market.
The implications for the AI market are significant. While the AI market is poised to grow by about 200% overall next year, the shift to inference could cost Nvidia as much as 5 percent of its market share, implying a revenue decline of up to $10 billion. The market will come to understand that there are better platforms out there for inference, and the market dynamic will adjust accordingly.
Theme 3
Open-Weight Models Rise
6) Open Models Rule
Open-weight AIs will come to dominate in 2025, outpacing proprietary models in adoption. Their adaptability and cost-effectiveness will democratize innovation and transform industries. When it’s released, Meta’s Llama 4 will essentially match GPT-5 in capabilities, and the debate over which is better will be academic. The full slate of Llama releases during the year will establish it and open-weight models generally as a de facto industry standard. The Llama models will reach a billion downloads by summer.
7) Sovereign AI Goes Global
More nations and enterprises will build their own Sovereign AIs and view their deployment as a strategic imperative in order to secure their economic future and stay competitive internationally. The US may join the club by building its own national AI, but not right away. It will treat AI as a means to achieve a geopolitical advantage, and AI-related policy moves will be notable in Washington as a rare example of bipartisan agreement in Congress.
Theme 4
Big Advances in Memory
8) Memory Optimization Drives AI Forward
2025 is the year that big memory and optimization will transform AI. Advances in chip memory and model architectures will enable systems to retain vast context, boosting Agentic AI, which can anticipate, plan, and execute with greater autonomy. Agentic systems are going to spur this need for big memory because they’ll require contextual awareness.
9) Energy Efficiency Redefines AI Hardware
Optimized memory architectures will reduce energy consumption in AI systems, driving down operational costs and easing the strain on datacenters. This will matter a great deal as power demand begins to outstrip supply late in the year, and hardware vendors will compete to boost their power efficiency.
It’s going to be an exciting year for innovation, and here at SambaNova we’re looking forward to showing you what we’ve been working on that will push the AI industry forward and help organizations achieve their AI ambitions.
