Things aren’t going so well for AI hardware startups.
After years of development, startup Humane launched a $700 wearable in early April that leans heavily on artificial intelligence. The original pitch for the Ai Pin was that you no longer need to juggle different apps; its operating system can “search for the right AI at the right moment,” allowing it to play music, translate languages, and even tell you how much protein is in a palmful of almonds. And because it doesn’t have a traditional display, the Ai pin was supposed to be a tiny tincture for the disease of screentime; smartphones were on their way out.
The pin has been panned. WIRED’s Julian Chokkattu scored the Ai Pin a 4 out of 10. Popular YouTuber Marques Brownlee complimented the device’s hardware design but still called it “The Worst Product I’ve Ever Reviewed … For Now.” The company has since massaged the message that it’s meant to replace your phone. Humane co-founder and chief executive Bethany Bongiorno has been fastidiously responding to displeased customers—and some fanboys—on Twitter, with apologies, assurances that improvements are coming, and video demos of the gadget’s UI, which replaces the smartphone in your palm by projecting lasers onto your palm.
Humane appears to have lost the thread on its own product launch, and it’s not alone. The cheaper Rabbit R1, which was sold for $200 as a generative AI “pocket companion” and generated a lot of initial excitement, has now been labeled “underwhelming,” “half-baked,” “undercooked” and “unreliable.” WIRED’s Chokkattu gave it a 3 out of 10, while some people have questioned the way the device handles logins for outside apps such as Uber.
These early hardware #fails aren’t unprecedented. Plenty of startups have overpromised in marketing and then built and shipped lackluster products. Competing in hardware is especially difficult in the age of Tech Giants, whose ecosystems rule over all. Developer Ben Sandofsky surmised that the Humane cofounders’ adherence to the “Apple Way,” or toiling in a secretive vacuum, is partly to blame. They spent years polishing that singular product the way a giant tech company would, he wrote in a blog post, but with $230 million in venture capital funding instead of billions in cash stores.
But both Humane and Rabbit appear to have made another error in judgment: Both were banking on AI excitement in the ChatGPT era to capture early customers and keep themselves out of the gadget graveyard. Instead, they rode the AI hype train straight into a non-working brick wall. It turns out generative AI doesn’t make hardware any less hard.
“To really create a great new AI device you have to have both hardware and software figured out, and the question with some of these startups is how much of that software layer is just a skin,” says MG Siegler, a partner at GV, Alphabet’s venture capital firm.
Sielger suggests that technology giants currently possess a greater advantage, as they can develop utilizing their own resources and can afford to absorb losses while correcting and improving new product versions. Whereas startups are struggling to introduce their resourceful AI products from scratch, corporations such as Meta, Google, Microsoft, and Apple can make use of existing teams and services to install AI assistants into infinitely wearable eyewear, manufacture mobile phones with generative AI search functionality, design specific keys for AI on their notebooks, and load their tablets with “immensely powerful” AI chips.
“Major technology firms are capable of making multiple attempts on a hardware product, which is a luxury that a startup might not be able to afford,” comments Jacob Andreou, an investor at Greylock who has spent several years enhancing products at Snap. “The likelihood of these smaller companies succeeding in securing future fundraising rounds, especially after launching a costly and unsuccessful product, is rather grim.”
Written by Reece Rogers
Co-authored by Ben Oliver
Steven Levy
Brenda Stolyar
Bethany Bongiorno, Humane’s CEO and cofounder, acknowledged in a statement that “it is always a big challenge to create a first gen product” and said the company had issued “stability updates” to improve its device. “Ai Pin and its Ai OS, Cosmos, are about beginning the story of ambient computing and there is a long way to go in the category,” Bongiorno said. In a statement provided by Rabbit, founder and CEO Jesse Lyu said that the company is trying to “quickly and constantly improve the product while listening to the feedback from our highly active community.” Rabbit has released three software updates since the first R1 users received their devices, he said.
Humane and Rabbit aren’t the only startups jamming new variants of AI into new hardware. Limitless AI, previously called Rewind, recently revealed a clip-on pendant described as “a memory assistant that transcribes audio recordings.” A pair of intelligent ear discs from Iyo, spun out of Alphabet’s moonshot lab X, is supposed to be a “therapist, coach and tutor, all controlled through voice” when it launches late this year. And an AI compass called Terra uses APIs from Google and ChatGPT to guide users as they’re walking and hiking. Its design will be open source, to encourage people to build their own versions of the device.
Most startups are utilizing AI to introduce screen-free user interaction and information conveyance, reducing the necessity for multiple mobile applications. These startups are hoping that free, open-source AI models will become more adaptable, efficacious, and run on-device. Additionally, they believe that AI cloud services will become quicker and more cost-effective as the technology continues to evolve.
However, an AI hardware startup that creates an effective problem-solving product still has to go head-to-head with large corporations that greatly influence consumers’ relationship with technology—simultaneously persuading users to adopt new interaction methods. Jason Rugolo, the brain behind the new AI gadget Iyo One, highlighted in a recent interview the control Google and Apple continue to exert through their mobile platforms. According to Rugolo, because these platforms are centered around their own graphical user interfaces, these interactions take precedence. The novelty of Iyo One lies in its model where conversation is the primary interaction, necessitating a divergent approach.
Rugolo also mentions the ever-changing language used in marketing these new products and suggests that the emphasis on “GenAI” could be a temporary trend. In his words, the foundation of natural language interaction is large language models, which can be termed as ‘GenAI’. The terminology differs based on the app’s function—a hearing enhancement app is likely to use ‘machine learning,’ while a translation app would use a large language model.
Christina Warren, a senior developer advocate at Microsoft’s GitHub and former technology journalist, draws parallels between the current influx of AI gadgets and the consumer wearable and Kickstarter-funded gadget craze of the 2010s. She indicates that similar to then, the current situation is being driven by newly available technology that simplifies the building process.
“There was Google Glass, Pebble Watch, Oculus Rift, the Ouya video game console. There was some Instagram photo frame that I bought,” Warren says. “The Kickstarter gadgets in general kind of became a meme. You knew most were going to flop.”
Reece Rogers
Ben Oliver
Steven Levy
Brenda Stolyar
During a certain period, the construction of many gadgets was profoundly influenced by Android, as they utilized the Android Open Source Project as their foundation and developed their unique launchers or UIs. This is akin to how modern gadget start-ups are incorporating APIs like ChatGPT and designing their proprietary software. According to Warren, Android was a major technological force during that era of devices, and Kickstarter served as the financial catalyst to launch them.
Warren notes that the intriguing gadgets that endured the 2010s were either invented or ingested by major tech corporations. Pebble succeeded in implementing its open-source smartwatch concept, but its technology was eventually acquired by Google through a Fitbit purchase, creating a concentrated piece of wearable tech. Oculus, a VR headset manufacturer, was invested in early to foster Facebook’s VR ambitions. Amazon essentially paved the way for the smart speaker category with Alexa, and Apple’s sleek version of a smartwatch emerged victorious. These three powerhouses reached trillion-dollar market values, deepened their engagement with hardware development, and even started manufacturing their own computer chips. For budding companies like Humane and Rabbit, simply labelling a product as “GenAI” is insufficient to overcome this hurdle.
Siegler suggests for any AI hardware start-up to thrive, they need to focus on brand reputation and, most crucially, maintain extreme simplicity.
“If you come out saying you’re going to create a better world, it’s way too grandiose,” he says. “And smartphones can do a lot of this stuff already. So you need to start out doing something as simple as possible, like a wearable that only invokes one AI model and has an element of purpose.”
Some aspects of building an AI wearable could get easier. Andreou believes that some AI hardware startups are likely to turn to original device manufacturers, obscure companies that make products for consumer brands to put their own stamps on or enhance with software, in order to offload some of the costs of manufacturing the product.
“You need to have one or two people in the organization managing hardware and outsource most of the rest to keep costs small,” he says. Hardware startups will also increasingly turn to a subscription model to boost revenue, he predicts. Some have already tried to do that—Humane charges $24 a month—but the product itself has to, you know, work.
Warren thinks that smaller, open-sourced AI models that can run directly on devices and require less computational power might also be an opportunity for fledgling companies with limited capital to inject AI into their products. “But the question is still then, what kind of hardware are you building?” she says. Right now some of the hardware makers themselves don’t seem to know the answer.
