Interaction Models: Mira Murati's New AI

The problem Thinking Machines wants to solve

The AI models available today operate according to a sequential logic. The user writes or speaks. The model waits. Then it processes and responds. This pattern, while functional, introduces a profound discontinuity compared to natural human communication.

Thinking Machines describes this limitation with clarity: «Today's models experience reality in a single thread.». In other words, the model perceives nothing until the input is complete. It does not see the user's hesitation. It does not grasp the tone of voice. It does not interpret the visual context.

Therefore, the announcement of the Interaction models is born from a precise ambition. The goal is to bridge this gap between artificial intelligence and authentic human collaboration. As reported by The Verge, Thinking Machines aims for models that «think, respond, and act in real time.».

What are interaction models: architecture and functioning

Thinking Machines' interaction models are designed to simultaneously process three input channels: audio, video, and text. Furthermore, they do so continuously, without waiting for the user to conclude their interaction.

This real-time multimodal approach represents an architectural leap compared to traditional large language models. In fact, current models—even the most advanced ones—treat each conversational turn as a discrete event. In contrast, an interaction model maintains an active and persistent perception of context.

In practical terms, this means the system can detect if the user is hesitating before completing a sentence. It can interpret a facial expression during a video call. It can adapt its response based on the emotional tone detected in real-time. Therefore, it's a model that doesn't just react, but participate.

To further explore the topic of multimodal AI and its technical foundations, the MIT Technology Review offers precise analyses on the evolution of these systems.

Who is Mira Murati and why is the market following her?

Mira Murati served as the CTO of OpenAI until 2024. In that role, she oversaw the development of GPT-4 and ChatGPT. Her departure from OpenAI garnered significant industry attention.

The Thinking Machines foundation has confirmed that Murati intends to build something structurally different. Not an alternative to ChatGPT. Rather, a new paradigm of human-machine interaction. Therefore, the market follows every announcement from the company with interest.

Analogous to what happened with other startups founded by former executives of major AI labs, Thinking Machines benefits from immediate technical credibility. However, the distance between an announcement and a commercially mature product remains significant. This is particularly true for such ambitious technologies.

According to the analysis of Gartner, multimodal AI technologies are in a rapid maturation phase. Consequently, enterprise adoption timelines are shortening compared to previous cycles.

Immediate Impact for Italian SMEs: What Really Changes

For an Italian SME, the concrete question is: does this development change anything today? The answer is complex.

In the short term, interaction models are not yet available as a commercial product. Thinking Machines has announced the direction, not the launch. However, the indirect impact is already measurable. In fact, announcements of this type accelerate the evolution of the entire AI ecosystem, including platforms already in use.

Specifically, companies operating in highly relational fields—customer service, consultative sales, internal training—should monitor this trajectory. Furthermore, those considering investments in AI solutions for their business, they must take into account this paradigm shift in planning.

At SHM Studio, we work daily with SMEs that wonder how to integrate artificial intelligence into their operational flows. Therefore, understanding where the technological frontier is moving is an integral part of our consulting approach.

The ongoing construction site: limits and unknowns

It is necessary to maintain a realistic perspective. Interaction models present non-trivial technical challenges. Processing audio, video, and text simultaneously in real-time requires considerable computational power. Furthermore, latency must be sufficiently low to make the interaction fluid.

Beyond this, privacy issues arise. A system that continuously perceives the user's visual and auditory context raises relevant regulatory questions. In Europe, the framework of the GDPR and the AI Act imposes precise constraints. Therefore, the enterprise adoption of these technologies will necessarily have to contend with the regulatory perimeter.

Finally, the question of the interface remains open. How do you design a user experience for a system that doesn't wait? How do you manage real-time interruption or correction? These are largely unresolved interaction design problems. For those working in web design and digital interfaces, it is already fertile ground for reflection.

What to do now: find your bearings without chasing

Faced with a technological announcement of this magnitude, the most effective response is neither passive waiting nor uncritical immediate adoption. On the contrary, it is useful to structure a conscious strategic posture.

First, it is appropriate to map business processes where real-time interaction could generate value. For example, technical support sessions, customer onboarding, staff training. Subsequently, it is possible to evaluate which tools already available approach this paradigm and experiment with them in controlled contexts.

For SMEs that want to structure a coherent digital strategy, the services of digital marketing and of SEO remain fundamental pillars. However, AI is increasingly permeating these areas. Therefore, ignoring it means forfeiting a growing competitive advantage.

Those managing campaigns on professional channels like LinkedIn can already leverage AI today to optimize targeting and messaging. Our services LinkedIn campaign and of Google Ads already integrate automated optimization logic. Likewise, the SEO copywriting Benefits from AI tools for semantic search and content structuring.

Outlook: where does this trajectory lead

In the 2027-2028 biennium, it is reasonable to expect that real-time multimodal models will become a standard component of enterprise AI platforms. Thinking Machines will not be the only player in this space. In fact, OpenAI, Google DeepMind, and Anthropic are all working on advanced multimodal capabilities.

According to projections from McKinsey, The adoption of generative AI in companies is set to accelerate significantly in the next two years. Consequently, SMEs that begin building internal skills and AI-ready processes today will find themselves in a position of structural advantage.

For this reason, SHM Studio accompanies its client companies not only in managing current digital activities but also in understanding the transformations underway. Those who wish to delve deeper into these topics can visit our blog o contact us directly for a consultation.

In summary, Thinking Machines' interaction models are a clear signal about the direction of AI. It's not yet time for operational adoption. However, it is the right time to understand, plan, and position yourself.