WeWard, an application that provides users with rewards for tracking their steps, is introducing a feature named “Walking Mode” that permits users to limit their access to selected applications until they achieve a specific step goal. This feature aims to encourage individuals to walk while simultaneously aiding them in decreasing their screen time if that is their intent.

For instance, if a user wishes to spend less time scrolling on TikTok or Instagram while ensuring they carve out time for a daily stroll, they could limit access to those apps until they walk 3,000 steps. The step targets and locked applications are adjustable.

Previously, WeWard motivated users to take walks by providing “Wards,” a virtual currency within the app that can be redeemed for cash, gift cards, or donations. Additionally, there is a gamified leaderboard feature, allowing users to engage in light competition with friends. However, incorporating features aimed at reducing screen time aligns well with the app’s purpose, as many users seek ways to curtail unnecessary phone and social media interaction.

Backed by tennis champion and angel investor Venus Williams, the France-originated app reports having 30 million users across 29 nations, which includes 4 million users from the U.S. The platform also claims it has been proven to enhance walking time by nearly 25%.

“We believe the next generation of products should be crafted to foster healthier habits in the real world, rather than just capture more attention,” stated WeWard co-founder Yves Benchimol in an interview with TechCrunch. “Walking Mode represents our contribution to that vision, and we aspire to stimulate a wider dialogue surrounding mindful design and how success is defined within the industry.”

WeWard claims that users spend merely a few minutes daily in the app, a statistic it considers advantageous, as the app does not aim to monopolize users’ attention.

While several rewards applications finance their payouts by gathering and selling user information to third parties, WeWard asserts that it does not participate in these activities. Instead, it generates revenue through in-app purchases, affiliate marketing, premium subscriptions, and advertising.

Kevin Weil, an experienced technology executive recognized for his tenures at Twitter, Meta, Planet Labs, and OpenAI, has been appointed to the board of Stoke Space, a highly backed Seattle startup developing reusable rockets to rival SpaceX.

“For me, it’s quite straightforward,” Stoke CEO Andy Lapsa stated to TechCrunch regarding his encounter with Weil when he co-founded Stoke in 2020 and subsequently joined Y Combinator’s winter program. “I came from an engineering background, launched a company, had no clue about fundraising. I didn’t understand how Silicon Valley operated. I lacked a network. Kevin [an early investor in the business with his spouse Elizabeth, via their fund Scribble Ventures] has all of that expertise and was instrumental in helping me consider fundraising and launching the company.

The two continued their discussions as Lapsa secured $1.34 billion — which included a $510 million Series D funding round in 2025 — to create a quickly reusable rocket that could take flight this year. Now, it seems that the moment is right for Weil to step into the board as a director to assist in further scaling the company. Stoke chose not to make Weil available for an interview, and he did not respond to TechCrunch’s inquiries.

Weil’s previous roles have centered around digital products and platforms, which are not clearly aligned with Stoke’s future plans. Most recently, he led OpenAI’s initiatives to expedite scientific research, departing the company after that program’s functions were distributed more broadly across the frontier lab in April. He had earlier acted as OpenAI’s chief product officer from June 2024 until October 2025.

Weil’s latest position raises one clear question: OpenAI’s Sam Altman was reportedly exploring a potential investment in Stoke last year, considering an investment in his own competitor to SpaceX. Could Weil serve as the connection between the frontier AI lab and a potential collaborator in space? Lapsa opted not to comment on “gossip and rumors” concerning OpenAI, asserting that Weil’s position is focused on Stoke itself.

Stoke is working on a rocket, Nova, designed to be entirely reusable and capable of multiple flights. This has never been achieved, with SpaceX coming closest with its massive Starship rocket. The technological hurdles of reusing a rocket — especially its capacity to withstand the intense heat of reentry into the Earth’s atmosphere from space — have dissuaded even the most financially equipped space investors. Jeff Bezos’ Blue Origin, where Lapsa previously worked, has considered the concept but hasn’t prioritized it.

However, SpaceX’s groundbreaking stock market launch — with much of its worth dependent on Elon Musk’s assurances that Starship will undertake operational missions this year — has validated Lapsa’s vision. Despite billions invested in new launch systems, there aren’t sufficient rockets available, and the next venture able to provide a reasonably priced rocket consistently is poised to profit significantly.

“The world is coming to realize that launch is not yet resolved,” Lapsa remarked. “The notion of full, rapid reuse seemed a bit far-fetched at that time…that has now become rather normalized, and people see the inevitability now.”

Interestingly, the concept of establishing distributed data centers in space to utilize solar energy and evade political constraints on Earth has inspired some venture capitalists. The primary barrier is the cost of launching all those computer chips into orbit. Space data centers “really only make sense with full rapid reuse,” Lapsa noted, which may serve as a critical differentiator for Stoke as its rocket begins operations.

Military contracts will also be pivotal to the company’s success, and Weil possesses experience connecting Silicon Valley and the Department of Defense; he was one of four tech leaders who enlisted in the U.S. Army Reserve to enhance recruitment and collaboration between the Army and the tech industry. Moreover, this isn’t his initial venture into the space sector. Weil was the president of Planet Labs, a satellite earth observation firm, for three years as it went public in 2021.

Regardless of what contribution Weil can make to the company’s strategy as it approaches the delivery of an operational launch vehicle, the company needs to execute.

“We’ve managed to mitigate a significant portion of the risk, but there’s more to tackle,” Lapsa stated. “We’ll put forth our utmost effort, and we’ll proceed when it’s prepared.”

Nvidia’s unmatched supremacy in the market is not finished, but new competitors and options are emerging from various sources.

ZML, an emerging French AI enterprise supported by Turing Award laureate Yann LeCun, has unveiled inference-performance software that enables numerous open source large language models to operate on a range of chips — including those from Nvidia, AMD, Google’s TPU, Apple Metal, and Intel Arc.

With the introduction of ZML/LLMD, the brand new LLM inference server, the firm aims to dismantle existing barriers and facilitate the use of different chips for AI purposes at their maximum achievable speed, and at times even quicker, as ZML founder Steeve Morin shared with TechCrunch.

As AI becomes more intertwined with our professional and personal lives, optimizing inference — or the processing of prompts — is increasingly overshadowing model training in significance, yet it often appears inconsistent behind the scenes, marred by software and architectural hurdles that lead to vendor lock-in, according to Morin.

The potential of attaining optimal performance across various chips represents a significant technological advancement, with the ability to disrupt the market amidst growing concerns regarding AI-related expenses.

ZML aspires to give businesses and cloud providers the choice to utilize a combination of chips, some of which might be more affordable or consume less power. “The aim is to return the control to people to construct their own systems and achieve genuine efficiency improvements that facilitate the spread of [AI],” Morin stated.

This software support could assist innovative AI chip producers, many of whom are based in Europe, noted Morin, mentioning companies such as Axelera, Fractile, Kalray, OLIX, Q.ANT, SiPearl, SpiNNcloud, and VSORA. However, he emphasized that the significant factor is not their geographical origin, but that ZML is capable of collaborating with them on “initiatives that have never been pursued before anywhere globally.”

Morin is not pessimistic about Nvidia. He acknowledged a positive relationship with the AI chip leader, which is preparing for the rise of inference.

Inference has attracted immense investment, leading to a trend termed the “inference gold rush.” Consequently, ZML faces rivals such as Baseten, recently valued at $13 billion; Inferact, from the developers of open source project vLLM; and RadixArk, the commercial entity behind SGLang.

Both vLLM and SGLang partially compete with LLMD, but Morin’s aspirations for ZML encompass a broader range. “We have arrived at a stage where we are co-designing silicon,” he expressed. He further credited ZML’s compact team of 20 as a key factor enabling the Paris-based startup to operate swiftly, with more launches on the horizon.

The fact that this small team is well-financed relative to its size also contributed to its success. Morin, who has a history as VP of engineering at Zenly — acquired by Snapchat for a significant sum in 2017 — raised $20 million from various venture firms including Harry Stebbings’ 20VC, >commit, AALVC, Drysdale Ventures, Xavier Niel’s Kima Ventures, Kindred Capital, LocalGlobe, and Puzzle Ventures.

In contrast to ZML’s initial public project, the inference-centric ML framework introduced in 2024 and updated in March, ZML/LLMD will not be open source. Nonetheless, it is debuting as a free offering with the intent of understanding usage patterns. “I’d prefer to assess and [then generate revenue] where it is most effective without foolishly stunting my growth due to excessive greed from the outset,” Morin remarked.

It remains uncertain when ZML/LLMD might transition to a paid offering and how its adoption will unfold. However, the startup’s cap table indicates that other founders are observing closely, including Dagger and Docker founder Solomon Hykes, Clément Delangue and Julien Chaumond from Hugging Face, as well as LeCun, now at AMI Labs. This reinforces the notion that Europe’s AI startups can now flourish locally. “I couldn’t establish ZML anywhere other than Paris,” Morin concluded.

SambaNova Systems, an AI chip enterprise, has secured $1 billion at a valuation of $11 billion during the initial close of its Series F round, spearheaded by General Atlantic, with additional investors anticipated to come aboard shortly.

“In the upcoming weeks, a few additional investors will be entering, and the second close is expected to wrap up soon,” stated Rodrigo Liang, CEO and co-founder of SambaNova, in an interview with TechCrunch.

This recent funding round arrives approximately five months after the startup, based in Palo Alto, California, introduced its SN50 chip and a $350 million Series E round in February. SambaNova was also reportedly in discussions with Intel regarding a potential acquisition that would value the company at around $1.6 billion, as per a December report from Bloomberg News.

When asked if the closure of its Series E and F rounds indicated that SambaNova, which was established in 2017, intended to remain independent, Liang was ambiguous. He noted that the company continues to receive interest. “We’re consistently approached.” The possibility of such an exit remains open in this dynamic AI landscape, according to the CEO, but growth and momentum will likely steer the company toward “going public at some point.”

SambaNova’s relationship with Intel, a supporter since its Series C and a participant in this latest funding round, has strengthened. Five months ago, the nine-year-old startup announced a multi-year collaboration with Intel aimed at enhancing AI inference development utilizing Intel’s Xeon chip. The two companies now co-develop products and market them together. “This establishes a strong connection with them that allows us to leverage Intel’s scale alongside our technology,” Liang remarked.

Along with the new funding, SambaNova announced it has been chosen by JPMorganChase as an “inference-infrastructure partner,” with its SN40L and SN50 systems set to facilitate secure, on-premises AI inference at the financial institution.

“Having JPMorgan Chase select SambaNova for their inference solution is significant,” Liang conveyed to TechCrunch. “It conveys a strong message to the banking sector that dependence on cloud services should not be absolute. These banks prefer heterogeneous [infrastructure].”

Liang indicated that the JPMorgan win signifies a trend in the wider market. Financial institutions “of JPMorgan’s stature” are now establishing their own private and secure infrastructure to execute inference on their most sensitive models, a trend he anticipates will extend beyond banking. He noted that enterprises and governments are “just beginning their AI journey,” with much of the growth thus far focused on model makers and frontier labs in tech, leaving what he termed “a tremendous revenue opportunity” still available.

SambaNova rolled out its SN40L in September 2023, available in the cloud, with on-premises availability starting November 2023. Its new-generation SN50, launched in February 2026, is expected to start delivering to customers in the latter half of 2026, with SoftBank as its initial deployment partner, Liang added.

Liang highlighted SambaNova’s advantage as “premium inference” enabling rapid execution of the largest models. Today’s frontier models encompass trillions of parameters, and he shared that SambaNova was specifically engineered to manage them at such a scale. The company places multi-trillion-parameter models on a single rack, facilitating efficient operation.

SambaNova identifies three categories of customers. The first includes sovereign clouds, where governments finance local partners to construct private clouds, a sector where Liang expects SambaNova to play a central role. The second category is neoclouds. The third consists of enterprises developing solutions for their internal use. Besides JPMorgan, they also identify Saudi Aramco, Intel, and various Japanese firms as clients.

SambaNova plans to utilize the funds to expand its operations and fortify its supply chain in response to what Liang described as an astonishing surge in demand. “We’re applying that capital to safeguard the supply chain,” he explained, emphasizing its importance to fulfilling orders and acquiring the necessary materials for the next 12 months.

Other investors joining the round include Seligman Ventures, T. Rowe Price Associates, and Capital Group. Both new and existing investors participated, including A&E Investment, Assam Ventures, Battery Ventures, Cambium Capital, BlackRock, Kabila Capital, QFO Capital, Qatar Investment Authority (QIA), Vista Equity Partners, and Volantis.

Final opportunity to apply

In response to significant interest, we’ve prolonged the application period for Startup Battlefield Australia to July 20.

If you’ve considered applying, act swiftly. There won’t be another chance for an extension.

A single application could transform everything

Since its inception in 2017, Startup Battlefield Australia has seen 26 alumni companies collectively raise over $147 million, with three successful acquisitions. They’ve garnered support from globally recognized investors — including Y Combinator, Blackbird Ventures, Square Peg Capital, Khosla Ventures, Microsoft, AirTree Ventures, Startmate, Techstars, and SOSV.

It all began with one choice: They submitted their application.

Reasons to apply now?

If you’re creating something bold, this is a quick route to the individuals who can propel your startup forward.

Chosen founders will present live to:

• Top-tier investors.
• Global media.
• Leading founders and operators from Australia.
• Potential partners, customers, and recruits.

This is beyond just a pitch competition. It’s an opportunity to gain visibility, credibility, and connections that may take years to cultivate.

What’s on the line?

On August 19, 2026, eight startups will showcase their pitches live at Stripe Tour Sydney.

The top three will be awarded up to $15,000 in Stripe fee credits.

The grand prize is even greater:

Automatic entry into Startup Battlefield 200 at TechCrunch Disrupt in San Francisco this October.

No secondary application. No additional rounds. Just a straight path to one of the largest startup platforms globally.

Who is eligible to apply?

We seek early-stage startups from Australia and New Zealand that are:

• Pre-seed to Series B.
• Developing a genuine product or demonstrating significant traction.
• Prepared to expand.
• Ready to share their narrative.

You don’t have to be a well-known name.

We’re in search of the next big thing.

The deadline has shifted — the opportunity remains

This extension allows you more time, but not by much.

Applications will now close on July 20.

If you’ve been holding back, this is your chance.

Ensure you submit your application by July 20.

Free to apply. No equity required. One chance that could alter everything.

On Tuesday, Meta introduced Muse Image, a new AI image generator developed by Meta Superintelligence Labs, the company’s specialized AI division. The functionality, which was internally referred to as Mango, is now accessible for free via the Meta AI app, as well as on Instagram Stories and WhatsApp.

Regrettably, the new model is already stirring up controversy.

What can you do with Muse? It appears that the use cases are akin to those of most other AI image generators — you will have the ability to create a multitude of whimsical, cartoon-like images, for example.

If you find yourself lacking inspiration and unable to create original prompts, Meta states that Muse offers “presets”— ready-made image prompts — to “inspire creativity.”

However, one particularly eyebrow-raising functionality enables users to alter another Instagram user’s images using AI, as long as that user’s profile is public. Users simply tag the person, allowing them to take their photo and utilize it to generate a new AI image.

One X user remarked after The Verge highlighted how potentially intrusive this is: “Incorporating real users into generated images without explicit consent is a privacy issue just waiting to explode.”

Meta’s policy indicates that “individuals may be able to produce content with your Instagram content using AI features at Meta” and that “you will not receive a notification regarding content created using AI features at Meta.”

Meta asserts that users “possess control” over this feature, emphasizing that there are settings available to prevent this type of appropriation of your images, should you choose to do so.

Muse also has other, less intrusive uses. One function is generating customized advertisements (AI has significantly entered the advertising space in the past year). Another is exploring ideas for interior decor — in a promotional video, a user utilizes Muse to envision how a secondhand couch could appear in their garage. This last feature is designed to connect with Facebook Marketplace, Meta’s popular platform for used furniture and accessories.

The model additionally offers prompt-based image editing, allowing users to create images to share among Meta’s apps and platforms.

“Request it to generate an image of you in front of a historical site, cleanly remove a photobomber from a background shot, or create a custom prompt to design a functioning QR code,” the company suggests.

Simultaneously, Meta is introducing various new AI effects for Instagram Stories, powered by Muse — notably, the same platform at the center of the photo-tagging debates mentioned earlier. These effects comprise customizable filters capable of altering existing photos.

Meta states that the use of the new AI model is free for “everyday creation,” although users will require a subscription plan upon surpassing a certain limit.

The company also indicated that Muse Video — presumably an AI video generator — is “currently under development.” TechCrunch has contacted Meta for additional details.

Over the past year, Meta has launched a variety of AI applications and services, including an AI assistant named Creator and Pocket, an application that can be used to vibe-code video games. The company has faced accusations of possessing an unclear AI strategy, even as it continues to plan significant investments in AI infrastructure this year as it expands its offerings.

Meta’s record on privacy contributes to users’ apprehension regarding Muse. The company previously paid a then-record $5 billion penalty to the FTC in 2019, after regulators discovered that the political consulting firm Cambridge Analytica had improperly harvested data from millions of Facebook users — without their awareness — to create voter-targeting profiles before the 2016 U.S. election. Facebook had been aware of the data misuse for years prior to its public revelation.

Separately, the company discontinued Facebook’s facial-recognition system in 2021 — a tool that automatically recognized individuals in images and videos — amid lawsuits and regulatory pressure concerning its acquisition of biometric data. Essentially, Muse’s photo-tagging functionality, which is opt-out by default, aligns with a pattern highlighted by users and regulators: widespread use of individuals’ data unless they actively deactivate it.

On Monday, Decagon’s CEO Jesse Zhang released a thought-provoking new perspective titled “Everyone is wrong about open source AI in the enterprise.” The article addresses one of the fascinating paradoxes of the current AI market: more advanced AI implementations are transitioning to lighter models, according to Zhang, even within his own organization. Yet, the overall expenditure on costly, cutting-edge models remains largely unchanged.

This presents a fresh viewpoint on the dynamics between frontier and open source models. Zhang argues that they are not rivals and that the achievement of open source models does not come at the cost of frontier laboratories. Rather, they represent two stages in the same evolutionary process, where expensive frontier models are utilized to validate use cases that can later be transferred to more affordable open source substitutes as they develop.

As established use cases migrate to lighter models, new applications continuously emerge — and the total spending on frontier models hardly decreases.

Zhang may not provide extensive data to back his claim, but finding the evidence is not challenging. Vercel’s AI gateway dashboard indicates that, in merely the past week, DeepSeek has surged to dominate the token volumes, processing slightly over a third of the tokens traversing the company’s infrastructure. Z.ai — the organization behind the well-regarded GLM-5.2 model — secured a noteworthy fourth place during the same timeframe. 

However, if you examine the total token expenditure, you’ll notice that Anthropic still represents over half of the overall AI spending on the platform. Although much of the recent change results from Anthropic’s own increasing prices, the proportion has decreased slightly in the last month, but not to a significant extent.

OpenRouter narrates a comparable tale, capturing a much broader (though slightly less enterprise-focused) market segment. DeepSeek V4 Flash stands out in overall usage, processing 5.3 trillion tokens each week. The leading frontier model, Opus 4.8, manages just over 2 trillion. OpenRouter does not rank models by total expenditure, but it indicates that the average token cost for Opus 4.8 is approximately 23 times higher than that of V4 Flash ($1.37 per million tokens versus just 6 cents), suggesting Opus likely still dominates expenditure.

These statistics do not even account for the latest addition, Nvidia’s Nemotron, which is expected to ascend to the forefront of the competition due to Nvidia’s robust connections and the model’s remarkable versatility.

These metrics may not definitively substantiate Zhang’s argument regarding AI life cycles, but they indicate that frontier labs like Anthropic aren’t dramatically affected by the rise of open source — not yet, at least. One possible reason is that the market for AI-relevant tasks is expanding rapidly enough that the leading models can retain their status simply by dominating early-stage deployments. As Zhang articulates, “The frontier labs will continue to dominate discovery. Open source will increasingly control production.” Another potential reason could be that, despite clients transitioning to open source, many use cases are complex enough that they cannot be fully supplanted by less expensive options.

Regardless, this dual-layer economy of models might evolve into a relatively stable aspect of the AI market.

As recently as last September, I was discussing the possibility that foundational labs would end up supplying coffee beans to Starbucks — serving merely as commodity inputs while the application layer enjoyed the rewards. Some elements of that prediction have materialized: Vertical AI initiatives have shifted to lighter models, for instance, and the financial dynamics of “GPT wrapper” startups have largely remained stable. 

Nonetheless, we are also observing that, token for token, frontier providers have managed to maintain a hold on the most lucrative portion of the marketplace — the premium token price. This doesn’t seem poised to change anytime soon.

Discord has recognized that an issue in its AI moderation framework erroneously banned over 8,000 users in the last two months, as harmless images—including spreadsheets, chessboards, gaming textures, plus white and gray transparent backgrounds—were wrongly identified as harmful material.

The corporation confirmed that this problem had been impacting accounts since May, with an extra 200 users banned over the weekend before the team identified and resolved the issue. All impacted accounts are in the process of being reinstated.

This situation underscores one of the escalating challenges related to AI-driven moderation as many platforms increasingly depend on automated systems to detect illegal or abusive content at a large scale.

In an extensive thread on X, Discord clarified that its automated safety system functions by comparing uploaded content against known harmful material databases. Although the technology aims to identify illegal content, the company admitted that false positives can sometimes occur. A human moderator assesses the content, but a glitch led to the immediate banning of affected accounts.

“We’re working on improved safeguards to ensure this doesn’t happen again,” the company stated. 

Our systems flag content by matching it against known harmful material. This type of similarity matching can result in false positives, which is why a member of our Trust & Safety team always reviews flagged content before any action is implemented.

The intended behavior is to…

— Discord Support (@discord_support) July 7, 2026

On X and Reddit, users reported being permanently banned merely for uploading images with square grid patterns. Many users theorized that Discord’s AI moderation tools have grown increasingly sensitive to grid-like designs because they have been used before to camouflage or conceal NSFW and child exploitation material from automated detection systems. 

Impacted users have expressed their anger on social media, with some claiming that permanent account bans based exclusively on automated detection can lead to serious repercussions, especially for individuals who depend on Discord for work, gaming communities, or long-distance social interactions.

“Losing a Discord account over something as unjust as this can be highly damaging and significantly impact users, and daily millions are affected by erroneous AI bans. This must be stopped,” a user on X commented. 

My account was unjustly banned from your platform due to a flaw in your AI automod misclassifying my GAME TEXTURES as CSAM. I need my account reinstated as I’m a game director and rely on Discord for all my communication. I have requested a review of my suspension.@discord @discord_support pic.twitter.com/QfAkCIJo6S

— JDBRYANT 🎂 TODAY (@jdbryantdev) July 4, 2026

Discord is not the only platform facing moderation issues due to automated systems. Last year, Instagram and Facebook Groups users reported numerous unexplained account suspensions that many suspected were due to AI moderation mechanisms. Although users pointed to automation as the probable cause, Meta never publicly confirmed if AI errors were to blame. Now, Meta’s Oversight Board is advocating for greater transparency.

Tumblr also encountered complaints from users last year who claimed their accounts were mass-suspended without clear justifications.