Technology

Figure’s humanoid robot takes voice orders to help around the house

Figure founder and CEO Brett Adcock Thursday revealed a new machine learning model for humanoid robots. The news, which arrives two weeks after Adcock announced the Bay Area robotics firm’s decision to step away from an OpenAI collaboration, is centered around Helix, a “generalist” Vision-Language-Action (VLA) model.

VLAs are a new phenomenon for robotics, leveraging vision and language commands to process information. Currently, the best-known example of the category is Google DeepMind’s RT-2, which trains robots through a combination of video and large language models (LLMs).

Helix works in a similar fashion, combining visual data and language prompts to control a robot in real time. Figure writes, “Helix displays strong object generalization, being able to pick up thousands of novel household items with varying shapes, sizes, colors, and material properties never encountered before in training, simply by asking in natural language.”

Quad 2.2025 02 20 11 31 01 — **Image Credits:**Figure

In an ideal world, you could simply tell a robot to do something and it would just do it. That is where Helix comes in, according to Figure. The platform is designed to bridge the gap between vision and language processing. After receiving a natural language voice prompt, the robot visually assesses its environment and then performs the task.

Figure offers examples like, “Hand the bag of cookies to the robot on your right” or, “Receive the bag of cookies from the robot on your left and place it in the open drawer.” Both of these examples involve a pair of robots working together. This is because Helix is designed to control two robots at once, with one assisting the other to perform various household tasks.

Figure is showcasing the VLM by highlighting the work the company has been doing with its 02 humanoid robot in the home environment. Houses are notoriously tricky for robots, given they lack the structure and consistency of warehouses and factories.

Difficulty with learning and control are major hurdles standing between complex robot systems and the home. These issues, along with five- to six-digit price tags, are why the home robot hasn’t taken precedence for most humanoid robotics companies. Generally speaking, the approach is to build robots for industrial clients, both improving reliability and bringing down costs before tackling dwellings. Housework is a conversation for a few years from now.

When TechCrunch toured Figure’s Bay Area offices in 2024, Adcock showed off a some off the paces the company was putting its humanoid through in the home setting. It appeared at the time that the work was not being prioritized, as Figure focuses on workplace pilots with corporations like BMW.

VLA Full Quality MASTER 21925A.2025 02 20 11 33 54 — **Image Credits:**Figure

With Thursday’s Helix announcement, Figure is making it clear that the home should be a priority in its own right. It’s a challenging and complex setting for testing these sorts of training models. Teaching robots to do complex tasks in the kitchen — for example — opens them up to a broad range of actions in different settings.

“For robots to be useful in households, they will need to be capable of generating intelligent new behaviors on-demand, especially for objects they’ve never seen before,” Figure says. “Teaching robots even a single new behavior currently requires substantial human effort: either hours of PhD-level expert manual programming or thousands of demonstrations.”

Manual programming won’t scale for the home. There are simply too many unknowns. Kitchens, living rooms, and bathrooms vary dramatically from one to the other. The same can be said for the tools used for cooking and cleaning. Besides, people leave messes, rearrange furniture, and prefer a range of different environmental lighting. This method takes way too much time and money — though Figure certainly has plenty of the latter.

The other option is training – and lots of it. Robotic arms trained to pick and place objects in labs often use this method. What you don’t see are the hundreds of hours of repetition is takes to make a demo robust enough to take on highly variable tasks. To pick something up right the first time, a robot needs to have done so hundreds of times in the past.

Like so much surrounding humanoid robotics at the moment, work on Helix is still at a very early stage. Viewers should be advised that a lot of work happens behind the scenes to create the kinds of short, well-produced videos seen in this post. Today’s announcement is, in essence, a recruiting tool designed to bring more engineers on board to help grow the project.

Technology

The Case for Custom eLearning Platforms: Why Organizations Are Making the Switch

aloe vera plant on grey pot on table with MacBook Pro and iPad

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.”

Pintarnya Founders Press Kit — image credits: Pintarnya (Founders of Pintarnya Ghirish Pokardas, Nelly Nurmalasari, and Henry Hendrawan)

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.