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March 03.2025
3 Minutes Read

Meet Mindy, the Privacy-Focused AI Assistant from Jolla's Founders

Two men demonstrating privacy-friendly AI assistant at cafe.

Revolutionizing AI with Privacy in Mind

The founders of Jolla, known for their efforts in the mobile market, are now diving into the world of Artificial Intelligence (AI). Their new AI assistant, developed in collaboration with sister startup Venho.ai, aims to provide users a privacy-preserving alternative to current cloud-based AI solutions. By allowing users to keep their data secure and private, this advancement may redefine the relationship between humans and technology.

Meet Mindy: Your New AI Companion

Introduce Mindy, the brand name for Jolla's AI assistant. This software integrates deeply with users’ daily applications, such as emails, calendars, and social media. Users can converse with Mindy, asking it to summarize emails, book meetings, or filter social media feeds. Jolla envisions Mindy as a personal aide capable of acting on the user's behalf, while ensuring no personal data is transferred to data-hungry corporations.

Pushing Back Against Tech Giants

As AI continues to shape the software landscape, Jolla co-founders Antti Saarnio and Sami Pienimäki express a determined vision: to disrupt today's dominant cloud giants. With a history of software and hardware development, they believe that a decentralized AI ecosystem can provide superior control to users over their own information.

Redefining Personal Data Privacy

The key selling point of Mindy is its commitment to user privacy. Unlike many contemporary AI assistants, Mindy doesn't rely on expansive data cloud storage. The assistant operates on smaller AI models that can be hosted locally, meaning that user queries and actions are processed without sending sensitive information to external servers.

From Concept to Creation: The Jolla Mind2

To complement the AI assistant, Jolla has released the Mind2, a device designed to support AI functionality without compromising privacy. The Mind2 operates like a mini-server—users can host their AI capabilities locally, allowing for even greater privacy assurances.

Addressing Challenges in AI Responsiveness

During a recent demonstration, TechCrunch noted that while Mindy shows great promise, initial queries had a slight lag time, an issue the Jolla team is addressing with ongoing optimizations. Users can look forward to faster response times as the team continues to refine their technology.

The Future of AI: Personalization and Control

As Jolla pushes for a larger slice of the AI market, they emphasize the importance of an individualized experience. With customizable avatars like Mindy, users can personalize their interactions with AI to align with their own preferences, reinforcing the concept of ownership over one’s digital experience.

The B2B Potential of Jolla's AI Assistant

Not only is Jolla targeting individual consumers, but there’s also growing interest from businesses looking for secure AI solutions. The company receives inquiries from telecom operators and others interested in the potential of Mindy as a home hub, reflecting the vast possibilities this technology holds.

Final Thoughts: Empowering Users in the AI Era

The launch of Jolla’s Mindy AI assistant marks a significant moment in the realm of privacy-focused technology. As users grow increasingly concerned about data collection, solutions like Mindy empower individuals with the tools to maintain control over their digital selves. Users can anticipate a subscription service that provides not just an assistant but a privacy-centric approach to digital interactions.

With prices starting at €699 for the Mind2 device, pairs with Jolla's service, privacy-conscious tech enthusiasts will want to keep a close eye on this promising development in the generative AI landscape.

Generative AI

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11.19.2025

Dismissing the AI Hype: Why We’re in an LLM Bubble Instead

Update Understanding the LLM Bubble: Insights from Hugging Face’s CEO In a recent address at an Axios event, Hugging Face CEO Clem Delangue presented a thought-provoking stance declaring we are not in an 'AI bubble' but an 'LLM bubble.' This distinction sheds light on the current state of artificial intelligence and the nuanced focus on large language models (LLMs), giving rise to a pressing dialogue on the sustainability of the technology's rapid advancements. The Inevitable Burst of the LLM Bubble Delangue predicts that the LLM bubble could burst as early as next year, a claim that has raised eyebrows within the tech community. He maintains that while some elements of the AI industry may experience revaluations, the overarching advancement of AI technology remains robust, particularly as we explore applications in areas beyond LLMs, such as biology, chemistry, and multimedia processing. For Delangue, the core issue revolves around the misconception that a singular model can solve all problems. “You don’t need it to tell you about the meaning of life,” he articulates, using the example of a banking customer chatbot. This specialized tool model demonstrates how smaller, task-specific models can be both cost-efficient and effective, catering directly to the needs of enterprises. A Pragmatic Approach in a Rapidly Scaling Industry Hugging Face, unlike many AI start-ups that are burning cash at unprecedented rates, has managed to maintain a capital-efficient approach. With $200 million left of the $400 million raised, Delangue argues this financial discipline positions his company well against competitors who are caught in a spending frenzy, chasing after the latest trends instead of focusing on sustainable growth. In fact, many tech giants are prioritizing profitability in this phase of rapid expansion, which Delangue symbolizes as a healthy correction expected in 2025 as enterprise demand begins shifting towards solutions tailored for specific applications rather than overreaching capabilities that general models like ChatGPT provide. This could herald a new era, empowering smaller teams to build more specialized AI solutions that outperform larger systems on specific tasks. The Bigger Picture: AI’s Potential Beyond LLMs The current focus on LLMs has overshadowed other essential aspects of the AI landscape. Delangue emphasizes that LLMs are merely a subset within a much larger field of artificial intelligence. Emerging applications in various sectors, such as healthcare and automation, show promising growth potential that could redefine industry standards of efficiency and performance. Moreover, as the market dynamics begin to shift towards inference rather than training, the demand for efficient AI models that can be deployed on-premises significantly increases. This will potentially ease concerns around data privacy, making the proposition of specialized models even more compelling for businesses looking for dependable and safe solutions. Preparing for the Future of AI While the looming burst of the LLM bubble may induce apprehension, it also opens avenues for strategic innovation and development in AI. As the industry continues to pivot towards practicality over hype, enterprises are encouraged to reconsider their approach to AI implementation. Delangue's insights serve as a clarion call for organizations to refocus their efforts on the effectiveness of solutions rather than solely on the size and scale of the models they deploy. In this shifting landscape, specialized applications of AI can enhance operational effectiveness, improve customer interactions, and ultimately drive more meaningful transformations across various sectors. Final Thoughts: Embracing a Diversified Future in AI If Delangue's predictions materialize, 2025 may not mark an end to AI innovation but rather an evolution towards a more diversified future driven by practicality and efficiency. Companies need to position themselves adeptly, embracing the necessity for specialization and efficient solutions as they navigate an increasingly complex technological landscape. The message is clear: understanding the LLM bubble helps illuminate the paths that businesses should take, aligning their strategies with the broader, evolving picture of AI beyond the current fad.

11.18.2025

Amid Super PAC Opposition, NY's AI Safety Bill Faces Crucial Test

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11.17.2025

How Renewable Energy Will Power the AI Data Center Boom

Update AI Data Centers and Renewable Energy: A Paradigm Shift The explosion of artificial intelligence (AI) technology is reshaping industries across the globe, and nowhere is this more evident than in the rapid expansion of data centers. According to a recent report from the International Energy Agency, the world is poised to invest a staggering $580 billion in data center infrastructure in 2025—outpacing even investments in new oil exploration—highlighting a significant trend towards a new era of technological dominance. The Growing Demand for Power This extraordinary investment comes amid escalating concerns about climate change and the energy consumption associated with generative AI. As we integrate AI deeper into our societal frameworks, these data centers are expected to utilize more power than ever before—potentially tripling their electricity demand by 2028. With the U.S. set to be a major consumer of this electricity, experts are questioning how to sustainably manage this growing appetitite while ensuring reliability and minimizing environmental impact. Renewables to the Rescue? Interestingly, the tech industry is pivoting towards renewable energy solutions. Prominent companies such as Microsoft and Amazon are already leaning heavily into solar energy for their data centers. For instance, Microsoft has contracted nearly 500 megawatts from multiple solar installations, while Amazon is leading the pack with 13.6 gigawatts of solar under development. These tech giants are shifting their focus not only for regulatory compliance but also due to the clear economic advantages that renewable energy offers—lower costs and quicker projects. Solving the Power Puzzle Innovations like solar + storage systems stand out as optimal solutions. These systems offer scalable, quick, and low-cost electricity sources. Additionally, they contribute to grid reliability, which will be crucial as the demand from AI continues to surge. Many analysts predict that the usage of such systems by major players in the tech industry will be pivotal in balancing demand and supply while calming environmental concerns. Balancing Act: Wind, Solar, and Emerging Tech The renewable energy landscape is also evolving to incorporate wind, nuclear, and even innovative technologies such as small modular reactors (SMRs). As tech companies seek diverse energy sources, they are creating partnerships that will not only support their data center requirements but also propel sustainable practices across the energy sector. These strategies emphasize the importance of multi-faceted energy solutions embraced by hyperscalers such as Google, whose investment in energy storage systems allows them to better manage when and how they consume power. The Social Impact of Data Centers While the promise of AI presents incredible opportunities for innovation and growth, the physical infrastructure demands of data centers can strain local electrical grids—especially in urban areas with growing populations. This challenge raises critical social discussions around energy accessibility, environmental justice, and the responsibility of businesses to ensure that their growth does not come at the expense of local communities. How cities adapt to these changes can shape the trajectory of urban development and job creation in the tech sector. The Future of AI Data Centers: A Dual-Edged Sword The economic incentives are clear—the companies involved stand to gain tremendously from a robust strategy that integrates renewable energy. However, without implementing sustainable practices and technological innovations, we could face dire consequences. As highlighted in reports, a staggering portion of energy consumption from AI-specific workloads could exceed the electricity requirements of entire nations. Therefore, investment in renewables must keep pace with AI growth. Conclusion: Harnessing AI for a Sustainable Future As we witness the rapid growth of AI, it is evident that the future of data centers hinges on our ability to transform energy consumption patterns. The shift to renewable energy not only presents a strategic business advantage for tech companies but could also play a significant role in addressing climate challenges. The choices made today about energy infrastructure will greatly influence the technological landscape of tomorrow—ensuring that AI's robust expansion does not compromise our planet’s health. Innovation must not be an afterthought, but a primary consideration as we forge ahead into this new era, paving the way for a sustainable future.

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