Long context modeling plays a crucial role in the development of AI systems capable of reasoning with extended sequences of information. Having spent years bootstrapping startups from scratch, I often see parallels between building scalable tech and creating something new in the business world, both need smart solutions to solve deeply ingrained challenges without overspending resources. Recently, Google introduced its Titans architecture and MIRAS framework, marking a shift away from traditional transformer models and promising to redefine long-scale AI contexts.
Transformers have long been considered state-of-the-art for understanding sequences in machine learning. They were celebrated for their structured approach, relying heavily on a token-by-token processing system through the attention mechanism. But here’s the issue: they struggle with speed and scalability for extremely long contexts, such as analyzing entire genomic sequences or handling documents with millions of tokens. This inherent bottleneck calls for innovation, and Titans may just provide the answer, particularly for entrepreneurs interested in deploying smarter AI models in business settings.
What Did Google Do Differently?
Titans combine the fine-grained attention provided by transformers with a deep neural memory system capable of scaling to longer contexts. These memory modules allow the architecture to update itself during inferential runs without requiring retraining, effectively enabling test-time learning. For those bootstrapping tech-enabled ventures, imagine a business model tool that learns and evolves based on your market data each time you input something new, this is the type of adaptivity Titans bring to AI.
At the core of this leap is MIRAS, which acts as a theoretical blueprint. It unifies all major sequence models under the umbrella of associative memory mechanisms. This concept simplifies complex problems by treating models such as transformers, RetNet, or Mamba-2 as variations of optimized memory systems. MIRAS uses a combination of learning algorithms, memory architecture, attentional focus, and retention gates to make this possible. For founders looking to integrate AI into their operations, understanding MIRAS can offer insights into how to manage scalable AI in your business, whether you’re handling customer data or predictive analytics.
What Matters for Entrepreneurs?
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Scaling Potential: For startups deploying long-context employees or analytics, Titans allow AI systems to decipher sequences far beyond current limits. Imagine document retrieval across millions of entries, Titans handle this better than alternatives like GPT-4 or linear RNNs, making it practical for industries like legal tech or healthcare.
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Speed Factor: Entrepreneurs building AI-powered tools often face resource limitations, and Titans deliver near-linear inference speeds while scaling their capacity. This is game-changing for smaller teams or bootstrapped startups that need efficiency.
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Practical Use: Titans have outperformed transformer models on benchmarks like the BABILong dataset, where recall accuracy across vast document lengths became a factor. This tells me it’s perfect for startups relying on accurate, long-range trend analysis, something many female founders leading e-commerce brands could use.
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Cost-Efficiency: The Titans architecture sidesteps the quadratic scaling cost of transformers. For those building businesses around AI capabilities, this could free up resources previously sunk into compute-heavy operations. It’s a strategic move business owners can appreciate.
How Female Entrepreneurs Can Apply This
European female founders, particularly those venturing into STEM, can learn from Google's approach to combining theory with application. For example, MIRAS could guide your strategy if you're creating platforms requiring adaptive analytics or memory structures that scale. The lesson here is not just about using Titans, it’s about thinking modularly, ensuring that innovations fit into your broader vision while remaining cost-effective.
- Start Small: Use Titans for mid-size contexts to maximize learning without wasting compute on theoretical extremes.
- Iterative Models: Your business doesn’t need the full MIRAS scope at its inception, focus on the four factors (architecture, bias, gates, algorithms) to adjust gradually.
- Collaborate Across Networks: Seek partnerships from labs that experiment with long-context models. Female founders in the Netherlands, for instance, can tap into local innovation hubs who study similar frameworks.
Mistakes to Avoid
- Blind Optimism: Entrepreneurs sometimes get caught in the hype around AI breakthroughs, but transitions like Titans need alignment with practical objectives. Consider phased testing before committing resources fully.
- Ignoring Updates: Titans thrive on test-time learning, but many businesses leave their models stagnant post-deployment, losing value from these adaptive algorithms.
- Treating Scalability as Optional: While startups often consider cost over vision early on, ignoring scalability can severely impact user satisfaction long term.
Lessons From Titans and MIRAS
I’ve seen firsthand how frameworks like MIRAS provide clarity in chaotic spaces. As entrepreneurs build systems reliant on AI-based decision-making tools, the idea of associative memory can serve as inspiration. Think of how data flows through customer management tools or revenue tracking systems, they can be seen as memory mechanisms, trained either on historical or real-time data. MIRAS shows us how discipline in organization yields better function. Female business owners can apply this strategy to their ventures by creating repeatable, scalable systems that grow alongside their needs.
If learning about the Titans model sparked curiosity, dive deeper into practical applications by reading the overview on Google's recent findings here: Google's work on long-context AI memory.
Wrapping It Up
Adapting AI innovations like Titans into entrepreneurial models doesn't require expensive experiments. Instead, it calls for focused integration of memory systems that won't just process data, they’ll adapt and evolve with it. For European female founders, leveraging frameworks like MIRAS and scalable technologies like Titans can position your business in the competitive markets of the future while keeping your operations efficient. Let’s stay ahead by picking insights that match our ambitions and translate to real-world results.
FAQ
1. What are Titans and MIRAS, and how do they improve AI systems?
Titans is a new AI architecture by Google that combines transformer-like precision with a deep neural memory system for long-term context handling. MIRAS serves as a theoretical framework unifying sequence models as variations of associative memory systems. Learn more about Titans and MIRAS
2. How does Titans differ from traditional transformer models?
Unlike transformers, which struggle with long contexts due to high computational costs, Titans uses a neural memory system to enable scalable, long-context learning with near-linear inference speeds. Explore the differences in Titan's architecture
3. What makes MIRAS unique for AI sequence modeling?
MIRAS unifies sequence models under associative memory optimization, identifying four core design choices: memory structure, attentional bias, retention gates, and memory algorithms. Discover MIRAS and its innovation
4. How does Titans handle test-time learning?
Titans adaptively updates its neural memory during inference using surprise-driven metrics, enabling it to learn from input data without retraining. Understand test-time learning in Titans
5. What industries can benefit most from Titans?
Titans is ideal for industries like legal tech, genomics, and healthcare that rely on processing extremely long sequences, such as documents or genomic data. Find applications of Titans
6. How does the Titans architecture improve cost-efficiency?
Titans overcome the quadratic scaling limitations of transformers, making them more resource-efficient for startups and small-scale operations. Explore Titans' cost-efficiency advantages
7. How have Titans performed in real-world benchmarks?
In tests like the BABILong benchmark, Titans showed superior accuracy in handling multi-million-token sequences compared to GPT-4 and linear RNNs. Check out Titans' benchmark results
8. What practical advice is there for entrepreneurs integrating Titans?
Start small by using Titans for mid-range contexts and gradually adapt MIRAS elements to keep costs sustainable. Collaboration with innovation hubs can also provide additional support. Learn practical integration tips for entrepreneurs
9. What are the risks of adopting Titans too quickly?
Jumping into Titans without phased testing or understanding its test-time learning capabilities can result in mismatched business objectives and wasted resources. Read about potential risks of Titans adoption
10. How does MIRAS relate to other sequence models like RetNet or Mamba-2?
MIRAS treats all sequence models, including transformers, RetNet, and Mamba-2, as variations of memory systems, categorized by design factors like memory and attentional mechanisms. Discover how MIRAS connects sequence models
About the Author
Violetta Bonenkamp, also known as MeanCEO, is an experienced startup founder with an impressive educational background including an MBA and four other higher education degrees. She has over 20 years of work experience across multiple countries, including 5 years as a solopreneur and serial entrepreneur. Throughout her startup experience she has applied for multiple startup grants at the EU level, in the Netherlands and Malta, and her startups received quite a few of those. She’s been living, studying and working in many countries around the globe and her extensive multicultural experience has influenced her immensely.
Violetta Bonenkamp's expertise in CAD sector, IP protection and blockchain
Violetta Bonenkamp is recognized as a multidisciplinary expert with significant achievements in the CAD sector, intellectual property (IP) protection, and blockchain technology.
CAD Sector:
- Violetta is the CEO and co-founder of CADChain, a deep tech startup focused on developing IP management software specifically for CAD (Computer-Aided Design) data. CADChain addresses the lack of industry standards for CAD data protection and sharing, using innovative technology to secure and manage design data.
- She has led the company since its inception in 2018, overseeing R&D, PR, and business development, and driving the creation of products for platforms such as Autodesk Inventor, Blender, and SolidWorks.
- Her leadership has been instrumental in scaling CADChain from a small team to a significant player in the deeptech space, with a diverse, international team.
IP Protection:
- Violetta has built deep expertise in intellectual property, combining academic training with practical startup experience. She has taken specialized courses in IP from institutions like WIPO and the EU IPO.
- She is known for sharing actionable strategies for startup IP protection, leveraging both legal and technological approaches, and has published guides and content on this topic for the entrepreneurial community.
- Her work at CADChain directly addresses the need for robust IP protection in the engineering and design industries, integrating cybersecurity and compliance measures to safeguard digital assets.
Blockchain:
- Violetta’s entry into the blockchain sector began with the founding of CADChain, which uses blockchain as a core technology for securing and managing CAD data.
- She holds several certifications in blockchain and has participated in major hackathons and policy forums, such as the OECD Global Blockchain Policy Forum.
- Her expertise extends to applying blockchain for IP management, ensuring data integrity, traceability, and secure sharing in the CAD industry.
Violetta is a true multiple specialist who has built expertise in Linguistics, Education, Business Management, Blockchain, Entrepreneurship, Intellectual Property, Game Design, AI, SEO, Digital Marketing, cyber security and zero code automations. Her extensive educational journey includes a Master of Arts in Linguistics and Education, an Advanced Master in Linguistics from Belgium (2006-2007), an MBA from Blekinge Institute of Technology in Sweden (2006-2008), and an Erasmus Mundus joint program European Master of Higher Education from universities in Norway, Finland, and Portugal (2009).
She is the founder of Fe/male Switch, a startup game that encourages women to enter STEM fields, and also leads CADChain, and multiple other projects like the Directory of 1,000 Startup Cities with a proprietary MeanCEO Index that ranks cities for female entrepreneurs. Violetta created the "gamepreneurship" methodology, which forms the scientific basis of her startup game. She also builds a lot of SEO tools for startups. Her achievements include being named one of the top 100 women in Europe by EU Startups in 2022 and being nominated for Impact Person of the year at the Dutch Blockchain Week. She is an author with Sifted and a speaker at different Universities. Recently she published a book on Startup Idea Validation the right way: from zero to first customers and beyond, launched a Directory of 1,500+ websites for startups to list themselves in order to gain traction and build backlinks and is building MELA AI to help local restaurants in Malta get more visibility online.
For the past several years Violetta has been living between the Netherlands and Malta, while also regularly traveling to different destinations around the globe, usually due to her entrepreneurial activities. This has led her to start writing about different locations and amenities from the POV of an entrepreneur. Here’s her recent article about the best hotels in Italy to work from.
About the Publication
Fe/male Switch is an innovative startup platform designed to empower women entrepreneurs through an immersive, game-like experience. Founded in 2020 during the pandemic "without any funding and without any code," this non-profit initiative has evolved into a comprehensive educational tool for aspiring female entrepreneurs.The platform was co-founded by Violetta Shishkina-Bonenkamp, who serves as CEO and one of the lead authors of the Startup News branch.
Mission and Purpose
Fe/male Switch Foundation was created to address the gender gap in the tech and entrepreneurship space. The platform aims to skill-up future female tech leaders and empower them to create resilient and innovative tech startups through what they call "gamepreneurship". By putting players in a virtual startup village where they must survive and thrive, the startup game allows women to test their entrepreneurial abilities without financial risk.
Key Features
The platform offers a unique blend of news, resources,learning, networking, and practical application within a supportive, female-focused environment:
- Skill Lab: Micro-modules covering essential startup skills
- Virtual Startup Building: Create or join startups and tackle real-world challenges
- AI Co-founder (PlayPal): Guides users through the startup process
- SANDBOX: A testing environment for idea validation before launch
- Wellness Integration: Virtual activities to balance work and self-care
- Marketplace: Buy or sell expert sessions and tutorials
Impact and Growth
Since its inception, Fe/male Switch has shown impressive growth:
- 5,000+ female entrepreneurs in the community
- 100+ startup tools built
- 5,000+ pieces of articles and news written
- 1,000 unique business ideas for women created
Partnerships
Fe/male Switch has formed strategic partnerships to enhance its offerings. In January 2022, it teamed up with global website builder Tilda to provide free access to website building tools and mentorship services for Fe/male Switch participants.
Recognition
Fe/male Switch has received media attention for its innovative approach to closing the gender gap in tech entrepreneurship. The platform has been featured in various publications highlighting its unique "play to learn and earn" model.
