The AI landscape underwent a seismic transformation in 2024, with frontier labs racing to outperform each other while navigating regulatory pressures and compute constraints.
The Clear Winners
- OpenAI maintained its technical edge with o1, which revolutionized complex reasoning through enhanced inference compute, achieving an unprecedented 83.83 score on AIME 2024 math competitions.
- NVIDIA dominated the hardware space, reaching a $3T market cap as its H100 and new Blackwell architecture became must-have infrastructure for AI development.
- Meta's Llama 3.1 405B marked a watershed moment, becoming the first open model to achieve near-parity with proprietary leaders across reasoning, math, and multilingual tasks.
The Fast Followers
- Claude 3.5 Sonnet and Google's Gemini 2.0 closed the performance gap with GPT-4o, particularly in coding and factual recall.
- Chinese labs like DeepSeek and 01.AI achieved competitive results despite sanctions, focusing on computational efficiency
- Microsoft's Phi-3 family pioneered efficient on-device AI deployment while maintaining strong performance
The Struggling Incumbents
- AMD and Intel failed to narrow NVIDIA's market lead despite significant investments.
- Traditional enterprise software vendors struggled to adapt their offerings to the AI era.
- Early-stage AI chip startups saw their collective value appreciation lag far behind NVIDIA's stock performance.
Looking ahead to 2025, several key battlegrounds are emerging:
Technical Frontiers
- Multimodal capabilities will become table stakes as video and 3D generation mature.
- Efficient inference and on-device deployment will drive competitive advantage.
- Open-source models will continue challenging proprietary solutions as larger companies will prefer to deploy their AI models in-house.
Market Dynamics
- Compute access and costs will increasingly determine market position.
- Custom AI solutions will replace generic offerings.
- A ton of VC-backed agentic AI startups will hit the market in 2025.
- Regulatory compliance will become a key differentiator.
Strategic Imperatives
- Hardware independence will be crucial for major labs.
- Vertical integration from chips to applications will accelerate
- International AI development hubs will emerge beyond traditional centers.
With proprietary and open-source foundational models converging in terms of performance, the race is no longer just about model performance - it's about building sustainable competitive advantages in an increasingly complex AI ecosystem.
If you're interested to read more about the business models that we think will dominate 2025, read our think piece on doing business in the age of AI:
Brand Management Gets an AI Upgrade
Brand.ai is changing how companies maintain brand consistency across their digital presence. Their "BrandOS" platform leverages advanced AI to:
Automated Brand Governance
- Analyzes existing content to extract brand patterns
- Provides real-time feedback on brand compliance
- Automates review cycles for marketing materials
Smart Asset Management
- Centralizes brand assets with intelligent tagging
- Enables dynamic asset updates across platforms
- Maintains version control with AI-powered tracking
Performance Analytics
- Measures brand consistency across channels.
- Tracks engagement metrics for branded content.
- Identifies opportunities for brand optimization.
Companies using AI for brand management are seeing significant efficiency gains, with review cycles reduced by up to 90% and improved brand consistency across channels.
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