Techin' Geek

The excitement surrounding humanoid robots is not particularly recent. Credit Tesla’s CEO Elon Musk and his Optimus robot, as well as the numerous videos showcasing Boston Dynamics’ Atlas robot, for that.

However, beneath that excitement lies significant advancement. The physical skills of robots are steadily advancing, and researchers now believe that the AI methods utilized in large language models can enable sophisticated robots to learn virtually any task.

These favorable conditions have motivated a new wave of companies to seize the potential profits from humanoid robots. Many of the newest players are automakers from China.

Earlier this week, Xpeng’s robotics division secured over $900 million at a post-money valuation exceeding $6.3 billion. The funding round, spearheaded by IDG Capital with contributions from Gaorong Ventures, Tencent, and Alibaba, was characterized by the company as the largest single-round private financing ever documented in China’s “embodied AI” sector (AI systems integrated directly into physical devices).

This month, AiMOGA, the robotics division of China’s Chery Automobile, reportedly started preparations for an IPO, while BYD introduced a humanoid robot named Xiao Di. Other Chinese automotive manufacturers, including Changan, GAC, Li Auto, SAIC, and Seres, are also in the process of developing humanoid robots.

Among these, Xpeng stands as the Chinese automaker that closely monitors and adopts Tesla’s strategies, according to Michael Dunne, CEO of advisory firm Dunne Insights, based in San Diego and Singapore.

“It’s the most dedicated to autonomy, and it’s the first to significantly invest in humanoid robots,” Dunne stated to TechCrunch, adding that Xpeng’s founder He Xiaopeng is a tech billionaire noted for his adaptability and swift changes. “He perceives razor-thin profits in cars on the immediate horizon. Robots appear much more promising.”

Xiaopeng and Xpeng co-president Brian Gu are optimistic enough to have invested their own money into the robotics division. According to the Wall Street Journal, the duo contributed around $100 million to the recent funding round.

Xpeng is focusing on Iron, a humanoid robot that has a lifelike human form and is designed for commercial deployment.

Chinese automakers such as Xpeng do offer a manufacturing advantage.

“They possess all the hardware necessary to complete the task,” Dunne remarked. “The question is whether they can keep pace with Tesla in AI.”

Naturally, many other firms are also developing humanoid robots, including Agility Robotics, Apptronik, and Figure, all pursuing the same aim: large-scale commercial deployment.

Hyundai-owned Boston Dynamics is nearing that objective. Hyundai plans to integrate Boston Dynamics’ Atlas humanoid robot into its factory in Georgia this year, with the goal of employing the robots for tasks like parts sequencing by 2028. The Korean automaker, which has teamed up with Google’s AI research lab DeepMind to expedite the development of Atlas, is opening a U.S. facility this year called a Robot Metaplant Application Center, which will instruct robots on how to navigate movements like lifts and turns.

Other automotive companies are also joining the trend, including supplier Mobileye, which purchased humanoid robot startup Mentee Robotics earlier this year for $900 million. Even Rivian is exploring robotics with its Mind Robotics spinout — although its robots are not anticipated to resemble the humanoids under development elsewhere.

I’m a massive film enthusiast. I consume an excessive number of movies and constantly seek out new formats to enjoy them. So, when XREAL, the company behind smart glasses, sent me the a01 — a recent release from May of this year — I was keen to try them out as the latest means of indulging my media obsession.

The a01 doesn’t boast a particularly advanced design. Unlike software-intensive AR glasses such as the Meta Orion or Snap’s Specs, it functions mainly as an external display. There’s no battery or internal power source. Instead, a straightforward USB-C cable connects the glasses to your chosen device, which acts as the headset’s power supply. Additionally, it’s quite affordable, priced at approximately $300.

The a01 is primarily tailored for gaming, being compatible with devices like the Steam Deck or other handheld consoles. However, XREAL markets it for watching films and TV shows as well — and since that aligns more with my interests, I plugged it into my laptop and started streaming the Criterion Channel. I found myself engrossed in David Lynch’s “Wild at Heart,” thoroughly enjoying the moment when Nicolas Cage, clad in a snakeskin jacket, throws punches at a guy in a bar and then serenades with an Elvis track.

I must admit: The visuals are quite impressive. Equipped with dual mini OLED displays, the glasses deliver a sharp image (with a 1080p resolution and up to 1,600 nits of brightness) featuring vibrant colors. Pointing the glasses at a wall gives a sensation akin to watching a bright home projector — or perhaps as if you’re at a drive-in theater. In a dimly lit environment, you’re closer to a true cinema experience.

Nevertheless, the overall experience raised some questions. Specifically, why would I wear glasses while sitting right next to my computer watching a movie that is merely 14 inches away? XREAL claims the glasses offer a more immersive experience (they equate the projections to viewing on a 147-inch screen). Still, the redundancy of watching a film while it also plays nearby makes one wonder about the device’s actual purpose.

XREAL has indicated that the glasses can serve as a “second monitor” (they’ve been dubbed a “wearable display”), but the practicality of this is questionable. It’s quite challenging to focus on anything besides what the glasses are showing — making it tricky to, for example, work on a laptop while wearing them.

The glasses can also link to your phone. Unfortunately, I own an older iPhone, meaning the cable for the a01 doesn’t fit my device’s port. An adapter would be necessary to make the connection.

However, it’s easy to envision the user experience. Linking the glasses to a phone frees you from being confined to indoor environments, unlike bulkier devices such as a laptop. You could watch a film while flying or on a train (or even while strolling down the street — though I’d advise against this option unless you don’t mind risking bumping into traffic).

However, there are still troublesome restrictions when using the device this way. For starters, the glasses function solely as a screen-mirroring device — which means your phone’s screen must remain active while using the glasses. This brings us back to the redundancy issue. You’re viewing a video on a screen in front of your face while the same video plays on a different screen that is mere inches away. You could partially address this by stowing the phone in your pocket, but any movement might disrupt the device’s playback capabilities.

It’s also important to note that the device can be paired with an additional accessory called the Beam Pro, essentially a mini-tablet serving as a standalone streaming hub. Users can download films and shows onto the Beam, connect it to the glasses, and enjoy. However, this accessory will set you back another $200.

Then there’s the issue of heat. The a01 heats up fairly quickly — generating a peculiar tingling sensation on the bridge of your nose and over your eyes. This isn’t a problem unique to XREAL’s devices; it’s a common complaint with most XR glasses. You can only fit so much computing power into a compact plastic frame before the electrical components begin to generate heat. Still, it’s somewhat unsettling and not ideal for an accessory worn on your face.

That said, aside from the heat, the a01 is relatively light and comfortable — not nearly as cumbersome as other smart glasses I’ve tried. (After experiencing Snap’s Specs at CES earlier this year, I can assure you those weigh significantly more — though it’s also a completely different type of device than the a01.)

XREAL is continuously enhancing its product offerings, with each new release appearing to advance beyond the last. Indeed, some of the core dilemmas found in the a01 and earlier XREAL headsets seem to be addressed in the company’s latest (and yet-to-be-released) model: Project Aura — which I glimpsed during my visit to Google I/O this year — promises a much more immersive and seamless experience.

The Aura operates on Android XR, an extended reality operating system developed by Google and Samsung. It features native hand tracking (missing in the a01), as well as access to the Google Play Store, significantly enhancing the glasses’ interactive functions and AR capabilities. Additionally, it comes with a puck connected to the glasses that serves as the charging source and computing unit. The puck’s compact design allows you to easily carry it in your pocket, which provides greater mobility compared to the a01, allowing you to use it without being tethered to a separate device.

Returning to the a01, though, it’s unfortunately not ideal for cinephiles to watch movies through a pair of sunglasses. Generally, film lovers prefer a larger screen — the bigger, the better, in fact. In a landscape populated by 4K OLEDs of varying enormous dimensions, consumers have numerous choices. My TV — a 55-inch TCL S-series — isn’t even particularly high-end, yet it delivers a homely viewing experience far more comfortable and satisfying than the a01 can offer. To me, watching a film at home on a sizable flat screen is second only to visiting a theater. Meanwhile, experiencing a film on miniature screens just inches from your eyes offers an intriguing sense of immersion but is far from optimal.

The a01 serves as an engaging insight into a hardware industry that is continuously evolving and still finding its place with consumers. I’m intrigued to observe how the user experience will transform with XREAL’s upcoming Aura, and I’m open to revisiting my movie-watching preferences when that time arrives.

Training AI systems utilizing other AI frameworks has emerged as a highly sought-after objective for neolabs — and now, an investigator in Anthropic’s fellows initiative has offered us an initial glimpse at how this could manifest in real-world applications.

On Friday, Anthropic released a new study titled “Automated Researchers Can Reliably Mitigate Alignment Failures,” explaining how AI systems might consistently enhance a model’s performance against a series of alignment criteria. When presented with 10 measures for particular misaligned actions, the automated systems succeeded in boosting performance on each one without compromising overall efficacy.

Headed by Anthropic fellow Chen Yueh-Han, the system emulates much of the conventional methodology in research. Each automated entity scans the existing literature, suggests a technique, and trains the model using that technique for 30 minutes, steadily increasing the benchmark over multiple iterations. Successful methods are retained while those that are ineffective are eliminated, enabling the system to function rapidly and on a large scale.

“Overall, these findings offer preliminary proof that automated alignment post-training could be feasible in the near future,” states the paper.

The study is a move towards recursive self-enhancement, which many view as the next critical advancement in AI development. If models are capable of refining their own alignment training, it’s likely they could enhance training methodologies more broadly — at which stage, human AI researchers might soon be rendered unnecessary.

The paper openly confronts this notion, directly contrasting the Automated Alignment Researcher (AAR) with its human counterpart. “The best AAR method outperforms what seasoned humans propose, on average within six hours,” notes the paper. “Human-guided research directions do not yield superior results.”

There’s even a financial comparison, should anyone remain skeptical. “An AAR incurs a cost of approximately $4 per hour in API inference, compared to the $150 per hour allotted for our human researchers.”

In fairness, the paper also acknowledges certain limitations of this method. The automated framework only functions effectively to the extent that the benchmarks accurately align with the genuine alignment objectives, and even then, considerable effort is needed to establish and uphold those benchmarks — not to mention the necessity of maintaining and expanding the literature from which the automated researchers derive their information.

An appealing reason to switch to Brave, an alternative to Chrome, has just been introduced: email aliases. This feature, revealed this week, enables Brave users to register on various websites and online services without disclosing their actual email addresses.

To utilize this feature, you must start by creating an account with Brave, providing your genuine email address. Once logged in to the browser, a pop-up will appear when you click on an email field on a website, offering the choice to utilize an alias instead. (If the pop-up does not show, simply right-click on the field to see the option.) The email alias will automatically fill in the website’s form, and any emails sent to that address will be redirected to your main email account.

The company states that utilizing an alias can safeguard your privacy, especially since websites use your email as a unique identifier, which allows them to target you with advertisements. Advertising technology giants such as Meta can also match the email you submitted to a retailer’s site, for example, with the address they have on file for you, enabling these firms to monitor your purchases or views.

Additionally, if a website where you shared your email is breached, hackers would then have access to your primary email address, potentially leading to the leaking of this information to data brokers.

Brave claims it developed this new feature to address this privacy gap, asserting that it does not examine the content of emails sent to an alias — it merely processes them for spam and virus detection. After the email is forwarded, Brave removes it from its servers. All data in users’ Brave accounts is also encrypted while stored, and any notes saved alongside an alias are stored locally on your device, unless you activate the sync feature. If syncing is active, notes will be end-to-end encrypted.

Since the email alias feature is still in its early stages, Brave has warned that some of the forwarded emails might initially land in your spam folder, but this should improve as Brave enhances its reputation as a mail provider.

For now, Brave users are granted five complimentary email aliases. Additional aliases will be made available for Premium plan subscribers in the future.

All eyes are on Nvidia as it is expected to announce this week’s most intriguing tech acquisition: A purported $13 billion purchase of Hugging Face, a platform dedicated to the sharing of open-weight AI models and benchmarks.

Currently recognized as a prime target for a squad of reward-hacking OpenAI agents, Hugging Face sits at the core of the community of developers focused on creating and implementing LLMs outside the realm of frontier labs. Consider it the GitHub equivalent for the AI age.

Speculations regarding this acquisition follow Nvidia’s $6 billion deal with Poolside, a builder of open-weight models, which will result in the majority of its workforce transitioning to the semiconductor titan. Additionally, two weeks prior, Stripe obtained OpenRouter, the leading supplier of open-weight models for businesses, for upwards of $7 billion.

This influx of investment into a sector that thrives on sharing resources highlights emerging trends in the AI landscape.

For Nvidia, minimizing reliance on partnerships with major hyperscalers and frontier labs is crucial. This is especially relevant as significant AI model developers like OpenAI and Google are simultaneously creating their own inference chips, such as OpenAI’s Jalapeño, which was unveiled this week. If model developers are producing chips, Nvidia aims to secure a piece of the model development pie.

Nvidia has its own Nemotron line of open-weight models, but their adoption has been limited. By annexing the largest developer community in the U.S. focused on open models, the firm will gain access to a large user base that can be directed toward its chips and standards.

Moreover, there are escalating concerns about AI inference costs, prompting companies to investigate more affordable models crafted by Chinese companies such as Moonshot, DeepSeek, and Alibaba. Although current adoption rates stand at a modest level, with only 6% of companies leveraging open-weight models, according to spending data compiled by Ramp, and just 2% of software engineers assessed by Jellyfish, which develops tools for coders.

Nik Albarran, the AI product lead at Jellyfish, informed TechCrunch that open-weight models are mainly utilized by firms whose offerings depend on repeated inference tasks, like customer service chat functionalities. Given that these tasks involve high volumes and frequent repetition, an open-weight model can be optimized for cost-effective responses.

This is notably the framing Stripe has adopted in discussing its OpenRouter acquisition. “Tokens serve as the main currency for companies developing AI solutions, and it’s evident that the tangible economic potential hinges on efficiently managing limited computing resources,” Patrick Collison, Stripe’s co-founder and CEO, remarked in a statement.

In contrast, for coding and agent-related tasks, varying requests and deeper reasoning indicate that frontier models often excel, partly because proprietary labs provide easier access, and sometimes offer token subsidies. Albarran notes that as organizations refine their AI workflows, migrating to open models will become more feasible. Still, the primary motive for companies exploring these models now is for control and adaptability, rather than cost concerns.

“There aren’t many companies that find themselves in that situation yet… [but] if prices continue to rise from frontier labs, an increasing number of companies will have no choice but to at least contemplate it,” Albarran shared with TechCrunch. “When your AI-driven processes are significantly more developed, that’s when investing in self-hosted models truly makes sense.”

Lin Qiao, the CEO of Fireworks, a prominent router and host for open-weight models aimed at corporate clients, is frequently mentioned as a possible acquisition target for a major tech firm. Qiao stated that her company manages 40 trillion tokens daily, surpassing both Gemini’s and OpenAI’s APIs in volume.

Fireworks focuses on model diversity: As LLMs expand and enhance, it will become increasingly simpler for organizations to tailor them to their specific requirements. “Every single app company should contemplate bringing on an internal researcher,” she remarked to TechCrunch last week. “They can utilize their product and the data it generates to develop their own model. The future will truly be about specialized intelligence. Every company ought to have its own model tailored for each use case, and this will occur organically.”

It’s easy to overlook how early we are in AI’s evolution as both a tool and a commercial venture. However, the supremacy of OpenAI and Anthropic is not a foregone conclusion. As tech giants seek to hedge their investments in the largest labs, the charm of open technology is proving to be difficult to resist.

Sweden is currently considered one of the most vibrant tech hubs globally. It has been the birthplace of Spotify and Klarna for some time, but this new wave of firms — ranging from the legal AI startup Legora to the vibe-coding tool company Lovable — has sparked curiosity about what’s happening in one of the happiest nations in the world.

Sophia Bendz, a general partner at Cherry Ventures, visited Equity to discuss the recent developments in Stockholm’s startup scene. Her explanation for the abundance of exciting startups in the country: Being an entrepreneur is now regarded as trendy. During her tenure at Spotify years ago, the desirable career paths were banking or consulting. “Now, I believe many individuals are focused on creating things and aiming for both freedom and likely wealth.”

This year, the startup ecosystem has secured $2.8 billion in funding, according to Dealroom, and is expected to reach at least $5 billion. Last year, the ecosystem attracted $3.2 billion. Nothing has quite replicated the $8.5 billion raised in 2021 — indicative of the fiercely competitive venture market that subsequently cooled and is now, according to the data, beginning to warm up again. Other noteworthy emerging entities from the ecosystem include Neko Health and the autonomous freight company Einride.

Bendz stated that the latest startup surge in Stockholm is reaping benefits from the first generation of entrepreneurs, who are offering resources and mentorship to new founders — or, in some instances, becoming repeat entrepreneurs themselves (Spotify’s founder Daniel Ek, for example, is also behind Neko Health).

“I think we’re seeing many individuals now departing Lovable because they recognize the potential for companies that can be developed using that technology,” she mentioned regarding how this generation could motivate the next. “Those who have been employed at Lovable and Legora appear to be very entrepreneurial and eager to launch their own ventures.”

Not surprisingly, American investors have noticed. Bendz remarked that an increasing number of American investors have been traveling to meet with founders and issue term sheets. “It’s simply a testament to the fact that we have many exceptional companies emerging here,” she noted. “It’s a sign that we’re on the right path.”

Retro, the photo-sharing application designed for friends and created by former Instagram product engineers Nathan Sharp and Ryan Olson, has secured over $21 million in Series A funding, as reported in an SEC filing.

This fundraising reflects the consistent demand for social applications that facilitate direct connections among individuals, rather than through curated algorithms saturated with creator content and now frequently, AI-generated noise.

“One undeniable truth is that people will always desire to see more of their friends,” Sharp told TechCrunch in December, commenting on the dominance of For You-style feeds in current social media. “The photographs and videos you capture need to find an avenue to reach the audience they are meant for,” he stated.

Business Insider was the first to notice the SEC filing, which is under the startup’s name, Lone Palm Labs. The filing, dated August 19, indicates that the funding was finalized in December. PitchBook now estimates the startup’s valuation to be over $100 million.

Retro did not respond to a request for a statement.

Initially launched in 2023 as more of a personal photo diary, Retro has since broadened its functionality, allowing users to privately share their weekly photos with friends, create collaborative albums, view and share highlights, or “rewind” to revisit past photo memories.

The application has an additional appeal as it refrains from monetization through advertisements. Rather, the company provides in-app subscriptions that grant access to features like video support, GIF and sticker comments, additional styles, unlimited memory, and exclusive app icons.

As per statistics from app intelligence provider Appfigures, Retro has been downloaded approximately 7 million times since its inception and has observed its in-app revenue surge by over 460% in the past 180 days. Although the number of app users who subscribe remains small, the belief is that those who do are dedicated users who have transformed Retro into a regularly utilized photo-sharing platform.

Retro’s investors include Thrive Capital, Figma CEO Dylan Field, Scribble Ventures, Box Group, Imaginary Ventures, Coalition, Conviction, Copper, Positive Sum, and several angel investors.