What's new in the world of AI?
1. GPT-4.5 Deprecation & Transition
API Sunsetting: OpenAI confirmed that the GPT-4.5 Preview API will be fully deprecated on July 14, 2025, with GitHub Copilot removing GPT-4.5 support by July 7 (source). This move signals OpenAI’s push toward consolidating its model offerings and encouraging developers to transition to more efficient, scalable alternatives.
Community Backlash: Developers voiced frustration with the short lifespan of GPT-4.5, especially those who had built apps or workflows dependent on its output style and tone (source). This highlights a growing concern over LLM stability for production applications.
New Options: OpenAI recommends transitioning to GPT-4.1, o3, or o4-mini, which offer improved performance and lower cost (source). These models are optimized for a wider range of tasks, including reasoning, retrieval, and coding.
Takeaways:
Developers and enterprise users must complete migrations by July 14 to maintain service continuity.
Businesses should use this transition to re-evaluate prompt strategies and optimize for efficiency and cost.
2. GPT-5 Previews & Rumors
Launch Window: Industry chatter suggests a potential July or August 2025 launch window for GPT-5 (source). If accurate, this would mark a major milestone with a new generation of capabilities.
Features: GPT-5 is expected to unify OpenAI’s GPT and o-series architectures into a single, more capable model. It may introduce enhanced reasoning, multimodal capabilities (e.g., image, audio, and video inputs), and dynamic context switching (source).
Implications:
Teams building long-term AI workflows should begin designing for multimodal and context-aware interfaces.
Expect OpenAI to introduce new pricing or tiered features under ChatGPT Pro+ or API premium tiers.
3. BERT++: NeoBERT & MaxPoolBERT
NeoBERT: A newly released 250M-parameter model offering extended 4K token context and top-tier performance on the MTEB benchmark (paper). This model is ideal for fast, cost-effective semantic search and ranking.
MaxPoolBERT: A novel technique that boosts classification accuracy by aggregating token-level representations across multiple layers, requiring no additional pretraining (paper).
Usage Tips:
NeoBERT is well-suited for search, embeddings, and RAG pipelines where performance-to-cost ratio matters.
MaxPoolBERT can improve NLP classification tasks in domains with limited training data or compute.
4. Multimodal & Agentic AI Advances
Google Veo 3: Introduces synchronized video/audio generation capabilities for realistic digital storytelling (source). This represents a major step forward in AI-generated multimedia.
AlphaEvolve: An open-source model designed to iteratively refine and optimize generated code and algorithms (GitHub). It shows how LLMs can now play a deeper role in improving their own outputs.
Agentic AI: LDV Capital’s recent essay outlines the future of AI systems that act autonomously, using reasoning and physics-based engines to navigate digital environments. This is especially relevant for developers creating autonomous tools, assistants, or customer service flows.
Recommendations:
Explore Veo and Gemini Vision for storytelling, marketing, or educational applications.
Use AlphaEvolve for optimizing algorithmic workflows or iteratively improving internal tools.
Prototype low-risk agentic workflows in areas like internal ops, scheduling, or document routing.
5. AI in the Wild: Industry Highlights
Rebuild Efficiency: OpenAI engineers claim they can now recreate GPT-4 from scratch using internal tools and just 5–10 engineers, a drastic reduction from the original development requirements (source). This emphasizes the increasing maturity of LLM toolchains.
Meta Delay: Meta has delayed its anticipated “Behemoth” model launch until Fall 2025 due to subpar performance metrics during internal testing (source). This signals challenges even for well-funded AI labs.
Turing Test Breakthrough: GPT-4.5 reportedly passed a triple-blind Turing test, fooling 73% of human evaluators into thinking it was human (source). This raises new ethical and regulatory considerations.
Strategic Trends Table
Trend | What It Means | Action Steps |
---|---|---|
GPT-4.5 Retirement | Faster model sunset cycles | Migrate apps, review contracts, update model references |
Unified Multimodal Models | All-in-one AI models are the new normal | Start prototyping for voice, image, and chat interfaces |
Encoder Model Comeback | BERT-based models are becoming relevant again | Replace legacy NLP with new lightweight models |
Agentic AI | AI is beginning to act autonomously | Begin experimenting with agentic internal tools |
MLOps Evolution | Model development is increasingly modular and replicable | Prioritize reproducible, containerized ML environments |
Rapid Action Plan
Complete GPT-4.5 migrations before July 14
Begin testing multimodal prompt compatibility in key workflows
Evaluate BERT-based models for new or updated NLP pipelines
Prototype an agentic assistant for an internal business process
Monitor OpenAI and Meta model launches to inform roadmap decisions
Further Reading
Summary: AI evolution is accelerating. With GPT-5 looming, agentic workflows taking shape, and foundational models like GPT-4.5 retiring at unprecedented speed, business leaders and developers alike must prepare for shorter innovation cycles and more autonomous systems. Now is the time to build smart, fast, and future-ready.
Matt Lawler

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Weekly AI Update | July 9th, 2025
Stay ahead with clear insights & strategic direction The AI world keeps moving fast—and this week was no exception. From agentic tools and LLM mashups