Another day, another new AI agent harness is released.
Only this time, it’s one that aims to solve a growing enterprise problem as AI agents proliferate: enabling greater developer control of agents and tools, while reducing cost.
TrueFoundry, a San Francisco B2B machine learning startup co-founded in 2021 by former Meta engineers, has released its own custom TrueForge harness under the permissive MIT License on Github. Thus, it can be used with any of a developer (or their parent enterprise’s) preferred AI models, forked, modified, self-hosted and incorporated into commercial products.
The company states in a blog post that when it used TrueForge paired with the open source GLM-5.2 LLM to successfully complete 11 of 14 tasks on DevRev’s Enterprise-Bench — testing multi-step tool use across CRM, issue tracking, and document management systems — it cost 75% less than achieving the same results with Anthropic’s Claude Managed Agents harness powered by Claude Opus 4.8 ($2.90 compared to $11.80).
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Using the same model in each harness, Opus 4.8, TrueFoundry still claims a cost savings of roughly 30% using TrueForge compared to Claude Managed Agents ($8.50 vs $11.80).
Why is TrueFoundry giving this powerfully efficient harness away for free?
“We’ve had this ask from a bunch of customers,” said Anuraag Gutgutia, TrueFoundry’s co-founder and COO, in an exclusive interview with VentureBeat. “You have an ability where you bring in agents and MCPs — can we also get something where you can actually launch these managed agents? I think that is the need we are satisfying. It is not a replacement. People will use this alongside other harnesses, like the cloud-managed ones or the commercial-provider-managed ones, but this will serve as a way for people to use them in a vendor-neutral way and also at a lower cost.”
Indeed, TrueFoundry already offers a paid “AI Gateway” for enterprises centrally controlling model and MCP access, credentials, permissions, budgets and observability. TrueForge, by contrast, handles what happens above that gateway: the loop that lets a model repeatedly reason, call tools, receive results and continue working until a task is complete.
For enterprise developers, the practical proposition is that they can start locally with a single command and SQLite, then move the same agent harness into a shared deployment using Docker Compose or Helm with Postgres and Redis.
TrueFoundry explicitly warns that the local configuration is intended only for use on a developer’s machine, not as an internet-facing production service.
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Gutgutia said the company ultimately wants its AI Gateway to become the common layer beneath whichever agents and harnesses an enterprise chooses.
“There will be a set of companies that will use our harness as the way to launch managed agents,” he said, while others may continue using Claude, other open-source harnesses or internal systems. “But all that traffic should still be flowing through our gateway.”
Context management is where TrueForge tries to cut waste
TrueForge’s architecture centers on context engineering — controlling how much information gets sent back into the model on every step of an agent run.
That includes delaying the loading of MCP tool schemas until they are needed, delegating isolated tasks to subagents, moving oversized tool results into files instead of stuffing them into the active context window, processing structured results through code, and automatically compacting long-running conversations.
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The documentation sets the default compaction threshold at 50,000 tokens, though it can be changed per agent.
TrueForge also treats the sandbox differently from runtimes that keep an agent inside an isolated environment throughout its run. The core agent loop remains on the TrueForge server; a sandbox is provisioned as a tool only when the agent needs to execute code or work with files. TrueFoundry says that reduces unnecessary compute and allows a server to run more agents concurrently.
The company argues those choices directly reduce model spending.
How TrueForge compares to Claude Managed Agents and other leading orchestration harnesses
Type / focus
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TrueFoundry TrueForge: General-purpose production agent harness designed for enterprise deployments.
DeepSeek Harness: Open-source agent harness, currently positioned as a developer preview.
OpenAI Codex CLI: Coding-focused agent harness designed primarily for software-engineering workflows.
LangChain Deep Agents: General-purpose agent harness built on LangGraph.
Anthropic Claude Managed Agents: Fully managed production agent runtime operated by Anthropic.
License
TrueFoundry TrueForge: MIT.
DeepSeek Harness: MIT.
OpenAI Codex CLI: Apache 2.0.
LangChain Deep Agents: MIT.
Anthropic Claude Managed Agents: Proprietary.
Price
TrueFoundry TrueForge: The open-source harness itself is free. Model, sandbox and infrastructure costs are separate. TrueFoundry also offers an optional commercial governance layer through its broader platform.
DeepSeek Harness: No harness license fee. Users separately pay for whatever model providers and infrastructure they use.
OpenAI Codex CLI: The CLI is open source. Underlying model/API or subscription costs are separate, OpenAI says around $100–$200 per developer per month, although actual spending varies substantially with model choice
LangChain Deep Agents: Open source, with model and infrastructure expenses separate. LangChain also offers optional commercial services through LangSmith.
Anthropic Claude Managed Agents: Claude tokens consumed plus $0.08 per running session-hour, with runtime metered to the millisecond.
Model flexibility
TrueFoundry TrueForge: Vendor-neutral and designed around bring-your-own-model support.
DeepSeek Harness: Multi-provider and not restricted to DeepSeek models.
OpenAI Codex CLI: Supports configurable inference endpoints, including OpenAI-compatible services and local-model options.
LangChain Deep Agents: Broad multi-provider support through the LangChain ecosystem.
Anthropic Claude Managed Agents: Claude-centric.
Deployment
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TrueFoundry TrueForge: Can run locally as a single process with SQLite, then move into a production deployment using Docker Compose or Helm with Postgres and Redis.
DeepSeek Harness: Designed for local or self-hosted operation.
OpenAI Codex CLI: Primarily a local CLI experience, alongside OpenAI-hosted Codex products and services.
LangChain Deep Agents: Can be self-hosted or deployed through LangChain and LangSmith infrastructure.
Anthropic Claude Managed Agents: Anthropic manages the runtime and infrastructure.
Key features
TrueFoundry TrueForge: MCP and tool orchestration, subagents, human approval checkpoints, persistent sessions, context compaction, large-result offloading, Code Mode, generative UI, tracing and a sandbox-as-a-tool architecture.
DeepSeek Harness: Pluggable models, tools, session storage and agent loops, along with sandboxing, permissions, approval gates and skills.
OpenAI Codex CLI: Agent loop, repository and file operations, shell execution, MCP tools, sandboxing, permissions, approvals and context management.
LangChain Deep Agents: Planning, subagents, skills, filesystem-based context management, persistent memory, human-in-the-loop controls, MCP support and multiple sandbox backends.
Anthropic Claude Managed Agents: Managed execution environments, persistence, tools, sandboxing and infrastructure for long-running agents.
Key differentiator
TrueFoundry TrueForge: Its strongest distinction is the combination of an open-source, vendor-neutral harness with a clear path from local development to a shared production runtime, plus an optional enterprise governance plane through TrueFoundry.
DeepSeek Harness: Emphasizes deep modularity. Major parts of the runtime, including models, tools, storage and the agent loop, are designed to be replaceable plugins.
OpenAI Codex CLI: Stands out as a highly developed software-engineering-specific harness rather than a general-purpose enterprise agent server.
LangChain Deep Agents: Benefits from the broader LangChain and LangGraph ecosystem and offers a mature open-source path for building general-purpose agents.
Anthropic Claude Managed Agents: Minimizes operational burden by having Anthropic manage the runtime, but trades that convenience for tighter model and platform coupling.
Open source does not automatically mean governed
For enterprise buyers, one of the most important distinctions is between TrueForge by itself and TrueForge connected to TrueFoundry’s commercial AI Gateway.
The open-source harness can run independently. But it does not magically inherit an organization’s enterprise access policies on its own.
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“If you are using just the open source version of our agent harness, yes, you will need to put the right controls therein or in front of some other internal control system,” Gutgutia told VentureBeat.
When paired with TrueFoundry’s gateway, the company says agents can inherit the identities and access controls already attached to models, MCP servers, tools, skills and other agents. Gutgutia described the gateway as the place where enterprise SSO, identity providers and granular permissions can be centrally enforced rather than reimplemented separately for every agent.
That distinction is likely to be important for platform engineering teams evaluating the project. TrueForge is free software; TrueFoundry’s governance layer is the commercial control plane around it.
TrueFoundry says NetApp was a beta user of the harness and contributed requirements during development. Gutgutia said NetApp’s IT organization has used the technology for incident response and faster ticket triage, while also exposing internal agents as self-service tools for developers. He also identified Automattic as an early user.
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Background on TrueFoundry and its business to date
TrueFoundry was founded in 2021 to help enterprises deploy and operate machine-learning models, including Kubernetes-based model serving, training and infrastructure management.
Its three co-founders — Nikunj Bajaj, Abhishek Choudhary and Anuraag Gutgutia — previously worked at Meta and WorldQuant, respectively.
Gutgutia said the founders’ common experience was working around mature systems where infrastructure and controls were designed to prevent costly mistakes — an idea they believed would become increasingly important as AI moved into production inside large companies.
As generative AI spread through enterprise software, TrueFoundry expanded from that MLOps foundation toward managing LLM applications and, increasingly, the models, tools and agents around them.
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By 2025, the company had made its AI Gateway a central part of the business: a layer sitting between enterprise applications and model providers that handles routing, authentication, access controls, observability, budgets, guardrails and failover.
That evolution has been backed by roughly $21 million in outside financing. TrueFoundry raised a $19 million Series A in February 2025 led by Intel Capital, with participation from existing investors Eniac Ventures and Peak XV’s Surge, as well as Jump Capital and angel investors including Gokul Rajaram and Mohit Aron. The round brought total financing to about $21 million, according to Intel Capital’s announcement.
At the time, TrueFoundry said its customer base had grown fourfold year over year and that it was managing more than 1,000 clusters for machine-learning workloads.
The business has since become increasingly oriented around large-scale enterprise AI traffic. In VentureBeat’s January 2026 coverage of TrueFoundry’s TrueFailover launch, the company said it had more than 30 paid customers worldwide, had exceeded $1.5 million in annual recurring revenue during the prior year and was processing more than 10 billion requests per month through its AI Gateway.
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Customers and deployments cited by TrueFoundry have included NetApp, Siemens Healthineers, ResMed, Automation Anywhere, Nvidia, Games24x7 and others; Gutgutia also named NetApp, Siemens, Synopsys and Automation Anywhere among Fortune 1000 organizations working with the company in his interview with VentureBeat.
TrueFoundry has also been expanding through acquisition. In June 2026 it acquired UK-based Seldon AI, a longtime MLOps vendor whose Seldon Core software has been used for production model serving and inference.
As the acquisition shows, rather than treating traditional ML, LLMs, tools and agents as separate infrastructure categories, TrueFoundry is trying to put them behind a common deployment and governance layer.
TrueForge extends that strategy upward into the agent runtime itself. Until now, TrueFoundry’s commercial center of gravity has largely been the control plane underneath enterprise AI workloads — deciding which users and applications can access which models and tools, routing requests, enforcing policy, monitoring spend and keeping services available.
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TrueForge gives the company an open-source runtime above that layer where agents can actually execute. Gutgutia described the relationship as complementary: organizations can run TrueForge independently or continue using other agent harnesses, while TrueFoundry’s longer-term business opportunity is to provide the common governance and infrastructure underneath whichever agents enterprises choose.
Three months after closing its $6.75 billion purchase of Press Ganey Forsta, Qualtrics is cutting jobs across the combined company — a reduction that the experience-management technology company says reflects duplication between two organizations that were built independently.
The cuts are global, including the company’s dual headquarters in Seattle and Provo, Utah, and its international offices. Qualtrics is not publicly disclosing how many jobs were cut, and did not break out numbers by office, region, or job function.
One clue: Qualtrics sent impacted Seattle employees layoff notices under the Worker Adjustment and Retraining Notification Act, or WARN, according to one copy reviewed by GeekWire. The notice covers workers at Qualtrics Tower, 1201 Second Ave., its Seattle headquarters.
The Washington law applies only to layoffs of 50 or more at one site — so at least that many jobs were cut at the Seattle HQ. As of publication time, Qualtrics had not appeared in the Washington or Utah state WARN databases, which can sometimes lag the notices to employees by a day or more.
Qualtrics CEO Jason Maynard
Individual employees learned their status by email Wednesday morning.
In a memo to employees, obtained by GeekWire, Qualtrics CEO Jason Maynard called the acquisition a “defining milestone” for the company but said it “meant making hard decisions about what the organization needed to operate and function as a single uniform team.”
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“Since the acquisition closed, we’ve gone function by function, team by team, to understand where we have overlap and determine what we needed to do to move forward as one company,” he wrote, noting that the decisions were “made based on the structure of our combined organization: the roles we need, the capabilities we are building toward, and where we have duplication.”
Qualtrics makes software that companies use to collect, analyze, and adapt to feedback from customers and employees, a category of technology that it branded “experience management.”
Current and former employees posting publicly Wednesday on LinkedIn and other forums described cuts spanning departments and offices, including Seattle, Provo and international locations, and hitting both the legacy Qualtrics and Press Ganey Forsta sides of the business.
The Press Ganey Forsta acquisition, announced in October and completed in May, added what Qualtrics called the largest healthcare experience dataset in the industry. Press Ganey Forsta, based in Indiana, was itself the product of earlier mergers, and its Forsta products competed directly with Qualtrics.
The cuts follow a leadership shakeup in April, when Maynard removed five senior executives and outlined a broader reorganization spanning marketing, customer operations, IT and corporate development. Maynard, who joined from Oracle, became CEO in February.
It’s not the first round of cuts under private equity ownership. Qualtrics cut about 780 jobs, roughly 14% of its workforce, in October 2023 under then-CEO Zig Serafin, who cited complexity from years of rapid hiring. It had cut about 270 jobs earlier that year.
Qualtrics has been owned by private equity firm Silver Lake and Canada Pension Plan Investment Board since 2023, when they acquired it for $12.5 billion. It was the second time the company changed hands in under five years, following SAP’s $8 billion acquisition in 2019 and a 2021 IPO.
The Ting FX EP-2350 by Teenage Engineering is a standalone microphone with a few extras, including samples and built-in effect presets that can be modified by the user. It also has a distinctive design, and [Sam Holland] does an in-depth teardown that offers some insights that are worth keeping in one’s back pocket. The large, side-mounted lever in particular is an interesting bit, but more about that in a moment.
Inside the device is a single PCB, which has a cutout in the middle for a pair of AAA cells. A Raspberry Pi 2350 drives the device’s functions, supported by various components which [Sam] identifies, although he mostly looks at everything from the perspective of a mechanical engineer as he critiques the design. It’s a clean-looking, intentionally low-fi design that belies how complex the device really is.
The multi-function, chunky, spring-loaded side lever is of particular interest. It has three sensors: two switches and a potentiometer. One switch detects when the lever is at rest, or depressed by any amount at all. The potentiometer mates with the pivot point of the lever, allowing the device to directly sense how far the lever is pushed. The last switch triggers when the lever is pushed all the way in. Together, it forms an intuitive input that combines powering on (the device wakes up from sleep mode as soon as the lever is pressed) with the ability to adjust effects in proportion with how far the lever is pressed, while also bottoming out with a distinct click that itself acts as an input signal.
One other interesting bit is the light pipes that carry light from multiple indicator LEDs to the outside of the device. A textured surface acts as a diffuser and helps the lit surface look smooth, while a coating of silver paint prevents light bleed and (probably) maximizes light transmission through the plastic. Hot glue makes a pretty good light pipe material but if DIY light pipes end up in your next project, sanding the exit surface and giving the rest a coating of silver paint just might be worth a shot.
A people-search tool that promises “private and secure” searches left more than 9 million image files exposed online, including photos of people’s faces. A security researcher found the unprotected database, according to reports by WIRED and Digital Trends.
The tool is ClarityCheck, a service that lets someone upload a photo to identify the person in it. Its website tells users that “your reverse image search is private and secure”. The researcher, Jeremiah Fowler, published his findings through ExpressVPN. Fowler is known for finding unsecured databases left open on the internet.
The exposed store held about 450GB of data and needed no password to open, Fowler reported. That is a large trove for a mid-sized consumer service. Many files sat in folders labelled “faces” and “profiles”. They included profile photos, screenshots and other images of adults, teenagers and children.
Fowler put the total at more than 9 million files. The scale is what stands out: a single misconfiguration left millions of faces reachable to anyone with the link.
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How it was exposed
The storage was reachable through a web address found in ClarityCheck’s own public website code, according to the reports. Search engines did not index that link, but the files behind it had no lock. The company has since restricted access, the reports said. Fowler notified ClarityCheck, and the company locked the store down afterwards.
Neither report said how long the data had been open before he found it. Fowler said he could not tell whether anyone else had downloaded the files, since the storage kept no public access logs he could review.
There was a second problem too. By changing certain ClarityCheck web addresses and entering a person’s name, someone could surface possible email addresses, phone numbers and physical addresses, WIRED reported. That required no special access. It is a separate weakness from the exposed image store, and it points at the service’s own lookup system rather than a storage bucket.
Fowler found no sign that anyone reached the database with bad intent before the company secured it, the reports said. So far, they have not connected the exposed contact details directly to the exposed photos. The two problems were separate misconfigurations, the reports said, one for the images and one for the personal details.
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Why this is sensitive
The nature of the service makes the lapse awkward. ClarityCheck is built to help people check strangers and decide whom to trust online. A leak of its users’ own uploads cuts against that promise. The service asks people to trust it with the very images they use to vet others. ClarityCheck markets the search as a way to spot catfishing and fake dating profiles, according to Digital Trends.
Digital Trends noted that a lapse involving its own users’ uploads is a particularly uncomfortable one for a service sold on trust and safety.
The people in the photos may never have used the tool. ClarityCheck lets a user upload someone else’s face to search for them. That means a person whose face sits in the database may have had no contact with the service at all.
Some of the images appeared to come from social media, dating profiles and screenshots, Fowler reported. That raises the prospect that people had no idea their faces sat in the store.
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He also said he found files with timestamps beyond ClarityCheck’s stated 14-day limit for keeping uploaded images. If accurate, that would suggest the service held some images longer than its own policy allows. ClarityCheck did not address the retention point in its statement, the reports said.
What ClarityCheck says
ClarityCheck disputed the description of the store as “publicly exposed”. In a statement to WIRED, the company argued that reaching the files required a specific, unindexed web address. On that basis, it said, the data was not simply open to the public. The company did not dispute the number of files, according to the reports.
The reporting pushes back on that defence. The files themselves carried no password, WIRED and Digital Trends noted, and Fowler found the address inside code on ClarityCheck’s own website. An obscure link is not the same as a protected one, Digital Trends wrote, since a researcher found it and others might too.
TNW has not independently verified the database. The account here rests on Fowler’s research and the reporting by WIRED and Digital Trends, and on ClarityCheck’s statement to WIRED.
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A wider pattern
Exposed face data is a recurring problem. In June, the group ShinyHunters published 45GB of Madison Square Garden records that included facial recognition data. Tools that scan faces are spreading, from shop cameras wired to police alerts to services that match a photo to a name. Each new store of face data becomes another target.
The stakes are rising as AI makes it easier to misuse such images. Researchers have warned that generated media has made impersonation and scams simpler to pull off. Analysts have also cautioned that the next privacy breach may not need to leak data in the classic sense to cause harm. A person can change a leaked password; no one can change their face.
Regulators have started to act on large lapses. South Korea fined the retailer Coupang a record sum this year over a major data breach. For the people whose faces sat in ClarityCheck’s store, the worry is simpler: their image was held by a service many of them had never used, and, for a time, anyone who found the link could see it.
Katalyst’s LINK spacecraft will still rendezvous with the telescope but will no longer tug it to a higher orbit.
NASA
The Neil Gehrels Swift Observatory is expected to re-enter and burn up in the Earth’s atmosphere later this year, after NASA has aborted the mission meant to tug it back up to a higher orbit. NASA has announced that Katalyst Space’s LINK spacecraft will no longer dock with the satellite and boost it to a higher altitude as planned. The agency blamed it on LINK’s ongoing attitude control issue, which started in late July.
If you’ll recall, NASA reported at the time that the spacecraft was having problems managing its orientation in orbit, causing it to spin helplessly. That led to sporadic communications with the spacecraft. There was also some loss in functionality to LINK’s thruster system. NASA and Katalyst were still optimistic last month that the spacecraft could accomplish its goal, but things have clearly changed since then.
Katalyst had less than a year to design a spacecraft for the Swift Boost mission, which launched in early July. Shawn Domagal-Goldman, the Astrophysics Division director at NASA Headquarters in Washington, said it was a “high-risk, high-reward mission” mission from the start. It was a first-of-its-kind attempt, and the team had very little time to try and rescue the Swift telescope, whose orbit is rapidly decaying due to an increase in solar activity in recent years.
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NASA’s SWIFT observatory launched in 2004 to study gamma ray bursts, but astronomers are now using it for several other purposes. The agency has been relying on it to obtain critical information quickly when a sudden cosmic event takes places. This mission was supposed to add a decade or so to its life. Going forward, NASA says it will prioritize finding “new options to react rapidly to cosmic events,” but it will use current missions to help fill the gap for now.
While LINK will no longer tug the Swift observatory to a higher orbit, it will still attempt to rendezvous with it. NASA and Katalyst plan to gather as much data as possible from the rendezvous operations to serve future satellite servicing missions.
“This is not the outcome we were working toward, but it does not change why this mission was worth attempting,” said NASA Administrator Jared Isaacman. “The team moved with extraordinary speed to give Swift a chance to carry out more science while advancing capabilities America will need for satellite servicing in the future. We are going to learn everything we can from LINK’s rendezvous attempt and put those lessons to work on the missions that follow.”
Forward-looking: Are you the kind of person who hates having blood drawn? In a decision that could potentially make that phobia worse or better, the FDA has approved the use of a robotic device that can draw blood from a patient’s arm – with no human assistance required.
Called Aletta, the robot begins the process by instructing the adult patient on how to position their arm. Once in the correct place, the patient or a supervisor presses a button to begin.
Aletta starts by using near-infrared light and Doppler ultrasound to find a suitable vein in the patient’s arm, distinguishing it from an artery. If none can be found, the process stops.
Once a suitable vein is found, the system will apply a tourniquet, prepare the skin, then insert the needle, dispose of it, and even apply a bandage. The supervising phlebotomist confirms that collection tubes are filled in the correct order and verifies that all tubes are adequately full following the procedure.
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“Activating small-talk mode”
If this all sounds concerning, the good news is that the FDA specifies that a supervisor trained in phlebotomy must begin and oversee the procedure.
So, why bother with a machine if medical staff need to be present? The agency writes that one phlebotomist can oversee up to three Aletta devices at the same time, which may help address the current phlebotomist shortage in the US.
“This authorization reflects the FDA’s commitment to advancing innovative medical devices that help meet a critical public health need while maintaining the safety and effectiveness patients deserve,” said Michelle Tarver, M.D., Ph.D., Director of the FDA’s Center for Devices and Radiological Health. “Blood draws are one of the most commonly performed medical procedures in the United States, yet patients may face delays due to a growing shortage of trained phlebotomists.”
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Some people aren’t going to be comfortable having a robot push a needle into their veins, of course. But the FDA says Aletta has multiple safeguards. One of these activates if the person moves too much during the procedure, causing the needle to automatically detach and the draw to stop.
Better than a robotic prostate examination machine
Additional onboard sensors can pause the procedure and alert the supervisor if other unsafe conditions are detected.
The FDA added that clinical data showed Aletta achieved blood draw success rates comparable to or higher than those of trained phlebotomists when it attempted a blood draw.
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Adeletta’s FDA approval is only the first step. It could be a while before the machines start appearing in medical facilities.
BrianFagioli writes: PINE64 has some very bad news for Linux hardware fans. PINE64 says it has no plans to produce additional Linux devices in the near future because of the ongoing DRAM and eMMC shortage. Future production will depend on component pricing after mid 2027, while existing PineNote and PineTab2 inventory could run out in roughly three months. The company says PineTime, PineVoice, and Pinecil production will continue as usual, but the outlook for its Linux hardware is much less certain. “That’s it for this post, all in all it’s a bit bleak for the Linux devices, but in the meantime PineStore still have a great lineup of MCU powered devices which will continue to expand with more exciting devices,” the company said.
RCS in Google Messages has stopped working for some users
The issue mostly seems to be affecting newly set up Samsung phones
Various fixes have been proposed, but the simplest and weirdest seems the most reliable
RCS (Rich Communication Services) is a worthwhile upgrade to SMS — it brings encryption, read receipts, and more, and it’s accessible via Google Messages on Android. Except right now, it seems not to be working for a number of people.
The issue most commonly seems to occur when swapping over to a new device, so people who’ve had a Samsung Galaxy S26 for a while with no issue, for instance, are seemingly less likely to run into problems than someone who just bought the phone and set it up.
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But in any case, a number of Reddit users report RCS failing to connect, in some cases followed by a 3100 error code. The good news is that there are several potential fixes floating around, and one of them is quite straightforward.
That fix, as highlighted in one Reddit thread, is to turn off RCS, connect to a VPN, then turn RCS back on, and hopefully it will reactivate as normal. You can safely turn the VPN off at this point. This Reddit post says that you should connect to a VPN in Paris, France, specifically, but elsewhere, users have claimed success by using other VPN regions, so it’s unlikely you need to choose Paris — we certainly can’t see why that would make all the difference.
Anecdotally, this method seems to have the highest success rate going by the replies on Reddit, with most users exclaiming variations of “I can’t believe this actually worked,” and that’s good, because not all the suggested solutions are as simple as this.
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The official suggestion
Some Samsung Galaxy Z Fold 8 users are reporting RCS issues (Image credit: Richard Priday / TechRadar)
So we’d suggest trying this method first, but if it doesn’t work, then Google’s own support team posted a suggestion too. They say you should update to the latest version of Google Messages, then turn RCS off, clear data for Carrier Services, restart your phone, and finally turn RCS back on.
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If that doesn’t work either, another user has posted a six-step process that involves stopping the Google Messages app, then removing your phone number from Google, followed by turning off two-step verification, turning off recovery phone, and removing Google Play Services updates, then turning Google Messages back on — after which, if RCS is now connecting, you should re-enable/update all of the above.
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This feels like a bit of a nuclear option though, and not all users found this method worked for them. So hopefully the weird VPN trick will solve the issue for you. Interestingly, this trick first emerged two years ago when some users were having similar issues. So, while we’re not sure why it works, it has a long history of solving the problem.
I wrote about Sony’s latest wearable cooler a few months ago, and I’ll admit that walking around with a gadget clamped behind my neck still isn’t exactly my definition of looking stylish. But scientists have just given me a pretty convincing reason to reconsider.
Researchers at Concordia University compared wearable face and neck fans against conventional bladed and bladeless desk fans, and found that targeting a small temperature-sensitive area of the body can provide surprisingly effective cooling. Wearable devices brought overall thermal comfort close to what larger desktop fans achieved while consuming less energy and creating fewer unwanted drafts for people nearby.
Your neck is surprisingly good at keeping you cool
Tazia Rahman / Concordia University
The researchers tested four personal cooling devices in a controlled office at 25 degrees Celsius, using a 23-segment thermal manikin capable of measuring skin temperature, heat loss, and overall thermal comfort. This study found that the reason wearable cooling works so well comes down to where the air goes.
Your face and neck account for only around 5.5% of your body’s surface area, yet they are especially sensitive to temperature. Directing airflow toward those areas allowed the wearable fans to achieve whole-body comfort comparable to a bladeless desk fan or a conventional bladed fan running at low speed. The face-mounted fan increased heat loss from the face by as much as seven watts.
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A full-size bladed desk fan still delivered the greatest cooling overall, so I wouldn’t throw yours away just yet. But it also created much higher air speeds that sent more unwanted airflow toward neighboring coworkers.
Sony may already be onto something
Sony takes the idea considerably further than the wearable fans in Concordia’s experiment. The £199 Reon Pocket Pro Plus sits against the back of your neck and uses two thermoelectric modules rather than relying solely on moving air. The company claims that its latest model delivers over 20% stronger cooling than its predecessor, with the cooling plate able to reach a surface temperature around 2 degrees Celsius lower under its test conditions.
Daniel Nim / Digital Trends
It also monitors your environment and automatically adjusts its cooling, while Sony rates Smart Cool mode for up to 15 hours of battery life depending on conditions and settings. Concordia researchers see a bigger benefit to this kind of targeted cooling. If individuals can stay comfortable with personal devices, offices could potentially run centralized HVAC systems less aggressively, reducing building energy consumption. This becomes handy for hybrid workplaces where cooling an enormous office for a handful of employees makes little sense.
So yes, wearing a miniature climate-control gadget around my neck will probably continue making me look a little geeky. But I’d much rather look geeky than spend another summer surviving this heat wave.
An anonymous reader quotes a report from NPR: Meta was infused with a culture in which employees obsessed over user numbers and consistently pushed safety to the side, according to Arturo Bejar, a former employee turned whistleblower, who testified today in the landmark child safety trial against the social media company. Only one man had the ability to change that, Bejar said: CEO Mark Zuckerberg. But he didn’t. “At the end of the day, it was the company culture that Mark had created that made it so that it was practically impossible to deliver features that addressed the wellbeing and safety issues that we’ve been talking about,” he said.
Bejar is a linchpin witness for a consortium of states led by California, Colorado, Kentucky and New Jersey that sued Meta, alleging violations of consumer and child data protection laws, and that the company lied to the public about risks its platforms posed. The attorneys for the states say Meta designed Facebook and Instagram to hook young users and to keep them on site longer thanks to features such as infinite scrolling and the “like” button. Meta has denied the allegations. In his opening statement on Tuesday, attorney Paul Schmidt argued that the company was sensitive to the risks to teens, sought to address them and did not deceive the public about them. The state attorneys have not yet said if they will call Zuckerberg as a witness.
Testifying in federal court in Oakland, California, for a second day on Wednesday, Bejar, who worked on safety issues at Meta for eight years, said he interacted with Zuckerberg dozens of times, and charged that Zuckerberg was not telling the truth when he made public denials that the company put profits over safety. In particular, Bejar addressed a widely-shared Facebook post Zuckerberg made in 2021 after another whistleblower, Frances Haugen, shared internal documents with The Wall Street Journal that highlighted risks to the mental health of teens. In the post, Zuckerberg said it’s “just not true” that Meta prioritizes profit over safety and wellbeing. “Based on my experience at Meta, that is not an accurate statement,” Bejar said. […] Bejar testified, at almost every turn the company chose policies that boosted usership and revenue over safety. Safety was “not a meaningful priority,” he said.
The company aims to lower AI costs by attaching each task to the model and hardware that best suits it.
Callosum, a UK-founded AI start-up that develops software to match specific AI tasks with the least expensive and most suitable models and chips, has raised $100m in early seed feeding.
The round was backed significantly by the UK’s Sovereign AI Fund and led by venture capital firm Atomico with additional participation from investors Plural and DCVC. The organisation also has a partnership with chipmaker Cerebras Systems and has deals with Rebellions Inc and Axelera AI.
Established in 2025, by two Cambridge University neuroscientists, Danyal Akarca who is the CEO and CTO Jascha Achterberg, Callosum software can direct specific AI tasks towards the models and chips best suited to the activity and financial requirements, as a means of showing that not every company requires high-end, powerful graphic processors or AI strategies.
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Callosum was the first investment to be disclosed by the UK’s Sovereign AI fund, which launched in April of this year.
Kanishka Narayan, the UK minister for AI, said, “AI is nothing without the chips that underpin it and the eye-watering demand for them is only going to grow. In the race to develop and use AI, success will depend not just on having access to those chips, but on using them as efficiently as possible.”
In the race to develop the most efficient, cost-effective and powerful chips, a range of organisations globally have invested significant time, money and effort into expanding their capabilities.
This week, UK AI hardware start-up Fractile announced it is in talks to raise funding of roughly $600m at a pre-money valuation of $6.5bn. Fractile aims to enable the scaling of cheaper AI token processing for faster model reasoning.
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US AI company Etched raised $700m in a new funding round led by US trading firm Jane Street. The organisation builds inference clusters to make AI inference faster, cheaper and more efficient.
In March of this year, global leader in the AI and chips space Nvidia, announced a new multi-year partnership with Thinking Machines Lab, which will be using Nvidia’s systems to train its AI frontier models.
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Inside the device is a single PCB, which has a cutout in the middle for a pair of AAA cells. A Raspberry Pi 2350 drives the device’s functions, supported by various components which [Sam] identifies, although he mostly looks at everything from the perspective of a mechanical engineer as he critiques the design. It’s a clean-looking, intentionally low-fi design that belies how complex the device really is.
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