As host of Lead with AI, I've spoken with countless innovators, but my recent conversation with Hina Dixit stands out as truly transformative for how we might interact with artificial intelligence in the future. Hina, the CEO and co-founder of Decompute, brings extraordinary credentials to her mission of democratizing AI compute access. With eight years at Apple working on security and AI projects, followed by leadership roles driving AI investments at Microsoft's Venture Fund and Samsung Next, she's seen the AI landscape from multiple vantage points. What struck me most during our discussion was how her journey from technical expert to venture capitalist to founder stemmed from a moment of clarity - witnessing innovative AI companies struggle to access computing power while billions of capable devices sat with untapped potential around the world. In this conversation, Hina introduced me to Decompute and its flagship product Blackbird, technologies poised to reshape our relationship with AI by bringing computation back to our personal devices and away from distant cloud servers.

The Problem: AI's Compute Bottleneck  

During our conversation, I learned how despite the explosion of AI capabilities, actual access to these technologies remains tightly controlled by a handful of cloud providers. During her time as a venture capitalist, Hina noticed a concerning pattern that I hadn't fully appreciated before - promising AI startups frequently stood in line for compute resources from major cloud providers like Azure, GCP, and NVIDIA. This bottleneck was slowing innovation across the entire AI landscape, as entrepreneurs with brilliant ideas couldn't access the resources needed to build and test their solutions.

Meanwhile, as Hina pointed out, billions of capable devices sit underutilized around the world. Our laptops, desktop computers, Mac minis, AI PCs, and other personal computing devices represent an enormous reservoir of untapped computing potential. The typical consumer device spends most of its time operating well below its maximum capacity, representing wasted computational resources that could be harnessed for AI.

This disparity between centralized cloud resources and distributed personal computing power sparked Hina's vision for Decompute. By enabling AI to run locally on our devices, her company aims to break the monopoly that cloud providers hold over artificial intelligence. This approach not only opens access but also addresses fundamental concerns about privacy and data security that become increasingly relevant as AI systems grow more sophisticated.

LaserTune: Making Local AI Viable  

The breakthrough technology that most impressed me during our conversation was LaserTune, Decompute's proprietary system that makes fine-tuning AI models as fast as RAG (Retrieval-Augmented Generation). In practical terms, this means that users can fine-tune an AI model on a 100-page document in just 10 seconds - all while keeping the process entirely local on their personal device. This dramatic speed increase makes it viable to perform sophisticated AI tasks like analyzing complex documents, processing financial data, or building personalized agents without connecting to distant cloud servers.

The technical innovation has impressed even seasoned AI investors. Hina recounted "Holy smoke" moments when showing the technology to prominent venture capitalists like Tim Tully from Menlo Ventures. Their immediate reaction was disbelief - "When are you loading your models? How can this be so fast?"

These capabilities extend beyond simple text processing to complex multimodal documents. One case study Hina shared involved financial services clients using Blackbird to parse entire SEC filings - documents that blend text, tables, images, and graphs - and perform sophisticated analyses entirely on their devices. Questions like "Who are my top 5% stakeholders?" or extracting specific financial figures that would baffle traditional local AI systems can be answered without sending sensitive data to the cloud, thanks to LaserTune's optimization capabilities.

The Right to Forget: Privacy in the Age of Infinite Context  

What I found most philosophically interesting in our conversation was Hina's concept of the "right to forget." As AI systems like ChatGPT move toward effectively infinite context windows, where models can remember every interaction users have ever had with them, Hina raises a fundamental question I hadn't considered before: Don't humans deserve a break from perfect memory?

In our human relationships, making mistakes, being forgiven, and moving forward is fundamental to our social experience. Yet in the AI world, the trend is toward systems that never forget, creating permanent records of our interactions, queries, and data. Hina argues that this represents a fundamental imbalance in the human-AI relationship, particularly when that data is stored on distant servers beyond our control.

While Europe has begun addressing some of these concerns through regulation, Decompute takes a more direct approach by keeping AI interactions local. When your data never leaves your device, the question of what happens to it on cloud servers becomes moot. This is particularly important for sensitive applications like analyzing personal finances, healthcare information, or confidential business documents - uses where many people currently avoid AI tools altogether due to privacy concerns.

Building Your Personal AI Ecosystem  

During our conversation, Hina outlined the six specialized types of agents that Blackbird users can deploy on their local devices:

• Financial Agent: Analyze personal finances, budgets, and financial documents

• Legal Documentation Agent: Process and generate legal documents while maintaining confidentiality

• Research Agent: Work with long-form documents, books, and research papers

• Coding Agent: Assist with programming tasks against local code repositories

• Meeting Agent: Record meetings locally and generate summaries and action items

• General Purpose Agent: Handle everyday tasks and questions

What impressed me most about this ecosystem is that these agents operate with zero connection to the cloud, ensuring that sensitive data remains entirely under the user's control. The platform is available for macOS, with Windows support rolling out imminently, making it accessible to virtually all computer users.

For businesses, particularly in regulated industries like finance where data privacy is paramount, Hina explained that Decompute offers enterprise solutions that maintain compliance while allowing AI adoption. The core platform enables companies to deploy AI capabilities without compromising on security or risking data exposure to third parties.

The user experience resembles working with cloud-based AI assistants, but with the crucial difference that all processing happens locally. This means no lag waiting for server responses, no privacy concerns about data leaving your device, and no subscription fees for ongoing cloud compute resources.

The 2030 Vision: AI Comes Home  

Looking toward the future, Hina painted a bold picture that genuinely excited me - by 2030, she predicts cloud usage for AI will drop below 25% as computation shifts primarily to local devices. She envisions a world where every device becomes an AI powerhouse, enabling Jarvis-like AI companions that run locally on phones, laptops, cars, and home devices.

This vision directly challenges the business model of major cloud providers, who currently profit from the AI compute boom. By shifting computation back to end-user devices, Decompute aims to democratize AI access while simultaneously addressing privacy concerns that become increasingly pressing as AI capabilities expand.

For businesses, this shift promises significant cost savings by reducing or eliminating cloud compute expenses. Companies can deliver sophisticated AI capabilities directly to their customers without ongoing cloud costs or concerns about compromising user privacy. This enables new business models and applications that would be prohibitively expensive or impossible under the current cloud-centric paradigm.

Try Blackbird Today  

After speaking with Hina, I'm convinced that Decompute represents a fundamental rethinking of how we interact with artificial intelligence. Rather than sending our data to distant servers controlled by tech giants, her vision brings AI home, putting control back in the hands of individuals and businesses.

If you're concerned about privacy when using AI tools, or if you're looking for ways to analyze sensitive documents without exposing them to the cloud, I encourage you to explore Blackbird as an alternative to traditional cloud-based AI services. The platform is available now at dcompute.run, where you can download it for macOS and soon for Windows as well.

As AI becomes more deeply integrated into our daily lives, the question of who controls our data and the compute resources that process it will only grow more important. Decompute's approach suggests a future where AI lives alongside us on our personal devices rather than in distant data centers - a vision that promises greater privacy, reduced costs, and broader access to these transformative technologies.