Technology
Buzzy AI startup Multiverse creates two of the smallest high-performing models ever
One of Europe’s most prominent AI startups has released two AI models that are so tiny, they have named them after a chicken’s brain and a fly’s brain.
Multiverse Computing claims these are the world’s smallest models that are still high performing and can handle chat, speech, and even reasoning in one case.
These new tiny models are intended to be embedded into internet of things devices, as well as run locally on smartphones, tablets, and PCs.
“We can compress the model so much that they can fit on devices,” Orús told TechCrunch. “You can run them on premises, directly on your iPhone or on your Apple Watch.”
As we previously reported, Multiverse Computing is a buzzy European AI startup headquartered in Donostia, Spain, with about 100 employees in offices worldwide. It was co-founded by a top European professor of quantum computers and physics, Román Orús; quantum computing expert Samuel Mugel; and Enrique Lizaso Olmos the former deputy CEO of Unnim Banc.
It just raised €189 million (about $215 million) in June on the strength of a model compression technology it calls “CompactifAI.” (Since it was founded in 2019, it has raised about $250 million, Orús said.)
CompactifAI is a quantum-inspired compression algorithm that reduces the size of existing AI models without sacrificing those models’ performance, Orús said.
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“We have a compression technology that is not the typical compression technology that the people from computer science or machine learning will do, because we come from quantum physics,” he described. “It’s a more subtle and more refined compression algorithm.”
The company has already released a long list of compressed versions of open-source models, especially popular small models like Llama 4 Scout or Mistral Small 3.1. And it just launched compressed versions of OpenAI’s two new open models. It has also compressed some very large models – it offers a DeepSeek R1 Slim, for instance.
But since it’s in the business of making models smaller, it has focused extra attention on making the smallest yet most powerful models possible.
Its two new models are so small that they can bring chat AI capabilities to just about any IoT device and work without an internet connection, the company says. It humorously calls this family the Model Zoo because it’s naming the products based on animal brain sizes.
A model it calls SuperFly is a compressed version of Hugging Face’s open-source model SmolLM2 135. The original has 135M parameters and was developed for on-device uses. SuperFly is 94M parameters, which Orús likens to the size of a fly’s brain. “This is like having a fly, but a little bit more clever,” he said.
SuperFly is designed to be trained on very restricted data, like a device’s operations. Multiverse envisions it embedded into home appliances, allowing users to operate them with voice commands like “start quick wash” for a washing machine. Or users can ask troubleshooting questions. With a little processing power (like an Arduino), the model can handle a voice interface, as the company showed in a live demo to TechCrunch.
The other model is named ChickBrain, and is larger at 3.2 billion parameters, but is also far more capable and has reasoning capabilities. It’s a compressed version of Meta’s Llama 3.1 8B model, Multiverse says. Yet it’s small enough to run on a MacBook, no internet connection required.
More importantly, Orús said that ChickBrain actually slightly outperforms the original in several standard benchmarks, including the language-skill benchmark MMLU-Pro, math skills benchmarks Math 500 and GSM8K, and the general knowledge benchmark GPQA Diamond.
Here are the results of Multiverse’s internal tests of ChickBrain on the benchmarks. The company didn’t offer benchmark results for SuperFly but Multiverse also isn’t targeting SuperFly at use cases that require reasoning.

It’s important to note that Multiverse isn’t claiming that its Model Zoo will beat the largest state-of-the-art models on such benchmarks. Zoo performances might not even land on the leaderboards. The point is that its tech can shrink model size without a performance hit, the company says.
Orús says the company is already in talks with all the leading device and appliance makers. “We are talking with Apple. We are talking with Samsung, also with Sony and with HP, obviously. HP came as an investor in the last round,” he said. The round was led by well-known European VC firm Bullhound Capital, with participation from a lot of others, including HP Tech Ventures and Toshiba.
The startup also offers compression tech for other forms of machine learning, like image recognition, and in six years has obtained clients like BASF, Ally, Moody’s, Bosch, and others.
In addition to selling its models directly to major device manufacturers, Multiverse offers its compressed models via an API hosted on AWS that any developer can use, often at lower token fees than competitors.
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Technology
The Case for Custom eLearning Platforms: Why Organizations Are Making the Switch
The corporate eLearning market has exploded in recent years, growing over 800% since 2000. As the demand for eLearning continues to accelerate, more and more organizations are finding that off-the-shelf solutions cannot keep pace with their training needs. This has led many companies to make the switch to custom-built eLearning platforms tailored specifically for their requirements.
There are several key reasons driving the demand for customized eLearning tools:
Greater Flexibility and Scalability
Generic eLearning software packages often impose rigid constraints that limit their ability to adapt to an organization’s evolving needs. Meanwhile, the “one-size-fits-all” approach fails to support the personalized learning critical for employee development. Custom platforms provide flexibility to add and modify features to match ever-changing business goals. As companies scale training across global workforces, custom solutions built on cloud infrastructure can scale seamlessly to handle growing demand.
Deeper Integration Across Systems
Smooth integration with existing HR, LMS, and other business systems is critical for optimizing training workflows. However, off-the-shelf tools rarely integrate well, creating data and process siloes. Custom platforms can tightly integrate role-based learning paths with core business applications, sync user profiles, enable single sign-on, and more. This level of integration catalyzes more impactful training function.
Better Data and Analytics
Generic software severely limits access to data insights that drive improvement. Custom platforms unlock a trove of analytics on content consumption, learner progression, platform adoption, and real-time feedback. Integrated analytics dashboards and APIs allow businesses to derive deep visibility across the learner lifecycle. These insights help continuously enhance learner experience, target development gaps, and demonstrate direct training ROI.
Enhanced Learner Engagement
For modern learners accustomed to consumer-grade digital experiences, poor platform usability quickly erodes engagement. Custom designs allow companies to incorporate familiar features from popular apps and websites while optimizing for their audience. Adaptive learning approaches further personalize content to individual styles and needs. With modular component architecture, custom platforms stay on the cutting edge of new modalities like AR/ VR to captivate learners.
Brand and Culture Alignment
Off-the-shelf tools impose a generic and often disruptive experience that clashes with existing brand identity and culture. In contrast, custom platforms allow organizations to carry over familiar styling, voice, and workflow patterns. Consistency in experience preserves brand recognition while smoother onboarding leads to wider adoption across all employee groups. Over time, the platform can evolve alongside cultural changes as well.
While custom elearning tools require greater upfront investment, for enterprise training needs, the long-term benefits far outweigh the costs. The ability to mold platforms to current and future needs results in greater leverage from learning spend.
As businesses demand ever-more from their learning technology, custom solutions provide the agility needed for true scale. Rather than forcing training functions into the constraints of generic software, custom elearning development keeps the focus on nurturing talent and capabilities. For any organization looking to drive workforce transformation through learning, custom elearning represents the way forward.
Technology
Pintarnya raises $16.7M to power jobs and financial services in Indonesia
Pintarnya, an Indonesian employment platform that goes beyond job matching by offering financial services along with full-time and side-gig opportunities, said it has raised a $16.7 million Series A round.
The funding was led by Square Peg with participation from existing investors Vertex Venture Southeast Asia & India and East Ventures.
Ghirish Pokardas, Nelly Nurmalasari, and Henry Hendrawan founded Pintarnya in 2022 to tackle two of the biggest challenges Indonesians face daily: earning enough and borrowing responsibly.
“Traditionally, mass workers in Indonesia find jobs offline through job fairs or word of mouth, with employers buried in paper applications and candidates rarely hearing back. For borrowing, their options are often limited to family/friend or predatory lenders with harsh collection practices,” Henry Hendrawan, co-founder of Pintarnya, told TechCrunch. “We digitize job matching with AI to make hiring faster and we provide workers with safer, healthier lending options — designed around what they can reasonably afford, rather than pushing them deeper into debt.”
Around 59% of Indonesia’s 150 million workforce is employed in the informal sector, highlighting the difficulties these workers encounter in accessing formal financial services because they lack verifiable income and official employment documentation.
Pintarnya tackles this challenge by partnering with asset-backed lenders to offer secured loans, using collateral such as gold, electronics, or vehicles, Hendrawan added.
Since its seed funding in 2022, the platform currently serves over 10 million job seeker users and 40,000 employers nationwide. Its revenue has increased almost fivefold year-over-year and expects to reach break-even by the end of the year, Hendrawn noted. Pintarnya primarily serves users aged 21 to 40, most of whom have a high school education or a diploma below university level. The startup aims to focus on this underserved segment, given the large population of blue-collar and informal workers in Indonesia.
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“Through the journey of building employment services, we discovered that our users needed more than just jobs — they needed access to financial services that traditional banks couldn’t provide,” said Hendrawan. “We digitize job matching with AI to make hiring faster and we provide workers with safer, healthier lending options — designed around what they can reasonably afford, rather than pushing them deeper into debt.”

While Indonesia already has job platforms like JobStreet, Kalibrr, and Glints, these primarily cater to white-collar roles, which represent only a small portion of the workforce, according to Hendrawan. Pintarnya’s platform is designed specifically for blue-collar workers, offering tailored experiences such as quick-apply options for walk-in interviews, affordable e-learning on relevant skills, in-app opportunities for supplemental income, and seamless connections to financial services like loans.
The same trend is evident in Indonesia’s fintech sector, which similarly caters to white-collar or upper-middle-class consumers. Conventional credit scoring models for loans, which rely on steady monthly income and bank account activity, often leave blue-collar workers overlooked by existing fintech providers, Hendrawan explained.
When asked about which fintech services are most in demand, Hendrawan mentioned, “Given their employment status, lending is the most in-demand financial service for Pintarnya’s users today. We are planning to ‘graduate’ them to micro-savings and investments down the road through innovative products with our partners.”
The new funding will enable Pintarnya to strengthen its platform technology and broaden its financial service offerings through strategic partnerships. With most Indonesian workers employed in blue-collar and informal sectors, the co-founders see substantial growth opportunities in the local market. Leveraging their extensive experience in managing businesses across Southeast Asia, they are also open to exploring regional expansion when the timing is right.
“Our vision is for Pintarnya to be the everyday companion that empowers Indonesians to not only make ends meet today, but also plan, grow, and upgrade their lives tomorrow … In five years, we see Pintarnya as the go-to super app for Indonesia’s workers, not just for earning income, but as a trusted partner throughout their life journey,” Hendrawan said. “We want to be the first stop when someone is looking for work, a place that helps them upgrade their skills, and a reliable guide as they make financial decisions.”
Technology
OpenAI warns against SPVs and other ‘unauthorized’ investments
In a new blog post, OpenAI warns against “unauthorized opportunities to gain exposure to OpenAI through a variety of means,” including special purpose vehicles, known as SPVs.
“We urge you to be careful if you are contacted by a firm that purports to have access to OpenAI, including through the sale of an SPV interest with exposure to OpenAI equity,” the company writes. The blog post acknowledges that “not every offer of OpenAI equity […] is problematic” but says firms may be “attempting to circumvent our transfer restrictions.”
“If so, the sale will not be recognized and carry no economic value to you,” OpenAI says.
Investors have increasingly used SPVs (which pool money for one-off investments) as a way to buy into hot AI startups, prompting other VCs to criticize them as a vehicle for “tourist chumps.”
Business Insider reports that OpenAI isn’t the only major AI company looking to crack down on SPVs, with Anthropic reportedly telling Menlo Ventures it must use its own capital, not an SPV, to invest in an upcoming round.
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