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CVS agrees to pay $315 million to settle Justice Department case over opioid prescriptions
The settlement resolves a lawsuit brought in 2024 that accused the healthcare giant of providing massive amounts of opioids and other controlled substances “to fuel its own profits at the expense of public health and safety.”
How is Microsoft's Magnetic Connect different from Apple's MagSafe for MacBooks?
Apple's MagSafe chargers are proprietary, and the charging port can't be used for peripherals. Microsoft's Magnetic Connect solves both of these frustrations.
AI Can’t Tell Real Science From Junk. That’s a Big Problem.
Artificial intelligence is in the news every day. It solves fundamental math problems by hundreds, hacks into highly protected networks, and outstreams Taylor Swift. AI is also supposed to lead us to…
Thunder’s Quietest Preseason Development Solves Major Offseason Loss
Sharp-shooting guard Jared McCain is emerging as a dynamic perimeter threat, utilizing off-ball versatility and veteran poise to preserve the floor spacing lost during a transformative offseason.
The 'Black Box' That Solves AI Fears, And The Stock Behind It
Xometry has the inside track to one of the remaining largely untapped online markets: the market for things that don't yet exist.
8 Best Gifts for Men Who Have Everything in 2026
Buying for the man who already owns the good version of everything is its own kind of design challenge. He has the watch, the pen, the television, the card holder. What he doesn't have is the version nobody else thought to make, the object that solves a problem he didn't know he had or simply
Ring announces its first smart lock, solving a major pain point for smart home users
Today, Amazon’s Ring subsidiary is announcing its first ever smart lock. It solves a key problem that looms over many...
Innovation That Solves: From Business Needs to AI Solutions
Targeted AI innovation transforms business challenges like hydrocarbon compliance into effective technological solutions, writes Jorge Mandujano.
Brother of Hayden Panettiere's boyfriend resolves court case after arrest
Zach Hickerson, brother of late actress Hayden Panettiere's boyfriend Brian Hickerson, has resolved a case that landed him behind bars earlier this month.
The Polish Pavilion Dissolves You in the Politics of Sound
At the Venice Biennale, whale songs become a means for communication, opening up a dialogue on accessibility.
Early Sun May Have Devoured A Super-Earth, Scientists Say
According to research, adding a swallowed planet to the Sun's early history solves these mysteries all at once.
Serbia dissolves parliament as snap elections called
Serbia will head to the polls in late October after President Aleksandar Vucic dissolved parliament following growing pressure from protesters demanding political change. However, Vucic plans to stand as a PM candidate.
August Monthly Review: ChatGPT In Epic
Death, taxes, another frontier lab healthcare launch inspiring truly insane LinkedIn takes. As much as I want to stay away, I repeatedly am the crewman unplugging his ears whenever we pass these sirens. So it’s not the first and probably not the last time we dial up the typewriter rather than tie ourselves to the mast. The full blow-by-blow timeline: Health API Guy is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe The End of the Standalone PHR (Jan 8): ChatGPT Health arrives for consumers, at the time powered by b.well. I was bullish on the approach in that the best way for the PHR to finally solve distribution was to meet consumers were they already are (i.e. When Horizontal Meets Healthcare (Jan 9): OpenAI for Healthcare puts out the shingle for enterprises, with SharePoint ingestion standing in for the EHR integration the product actually needed. Another One: Anthropic’s Healthcare Debut (Jan 16): Claude's version, on HealthEx rails instead of b.well, with Agent Skills for FHIR development as the one true vertical-specific investment. ChatGPT for Clinicians: The Trap Sprung (Apr 24): OpenAI filled in the missing GTM middle with a free product for verified clinicians, effectively peeling the enterprise wrapper off ChatGPT for Healthcare and taking the PLG fight directly to OpenEvidence. OpenAI’s Second Attempt at Health (Jul 31): a relaunch of their patient specific app, now branded Health in ChatGPT, where the privacy partition came out, the connectors thinned, and b.well disappeared in favor of first-party FHIR work against a smaller network Beyond a Shingle So what was announced now? Today, we’re introducing a new electronic health record integration that brings authorized patient context from Epic into ChatGPT for Healthcare, along with the Healthcare Public Data plugin for direct, structured access to official healthcare datasets like PubMed, DailyMed, and CMS Coverage. Together, these capabilities bring ChatGPT closer to the systems and sources healthcare teams trust, while supporting the controls and compliance healthcare work requires. The core portfolio is unchanged from prior announcements we delineated and discussed (aside from the relaunch of patient-facing). Since trade publications still seem to be confusing them by using the wrong names: Enterprise sales motion: ChatGPT for Healthcare Protecting their core product / PLG: ChatGPT for Clinicians Consumer/patient-facing product: Health in ChatGPT So really, this is a feature release (specifically for ChatGPT for Healthcare when it comes to EHR integration). What’s cool about it, though, is that we are moving beyond just putting out a shingle. Everything in the January enterprise launch was horizontalizable: Horizontal tech companies thus generally start verticalization with their “putting out a shingle phase”. Telling the world you’re open for business as a horizontal tech company reliably attracts early inbound interest from buyers who are already trying to force-fit horizontal tools into domain-specific workflows and are eager for any signal that the vendor intends to support their use case more directly. Nothing was really vertical specific, which is exactly what you'd expect from the ultimate hypergrowth horizontal company dipping their toes into specific industries. But eventually you have to stop changing the sign on the door and start changing the product. Can you guess where the horizontal product was going to run out of road? This is the core dilemma writ large: verticalization requires differentiation, while scale economics of consumer and horizontal push toward unification. I’ve buried the lede so deep here it will be painful to some readers, but what should be shocking to no one is that my perspective is that EHR integration is the only path that meaningfully resolves this tension for ChatGPT for Healthcare. Integration with Microsoft Sharepoint is fine, but it is categorically insufficient for any product that hopes to influence clinical decision-making. SMART Money Well here we are, eight months later! Real vertical investment has begun, which surprised a few people. One friend in the industry messaged me: “Absolutely no way Epic gave ChatGPT API access.” Looking forensically at the announcements, the integration is notably read-only across appointment notes, laboratory results, medications, and specialist documentation. So while I’m not a betting man, I'd wager the house this is a SMART on FHIR launch: That sounds a lot like USCDI! The recommended path for the workflow they outline would be SMART on FHIR Their Health AI lead’s post is evocative of both standalone and EHR launch SMART, which another termed “ChartGPT” and “EHR Plugin” The implementation burden for SMART on FHIR is the lowest of the available integrative paths This is the team who literally did patient-facing SMART on FHIR with Epic last month Most importantly, if you’re a horizontal company, you generally still haven’t taken the full plunge and thus (overly) value reusability. SMART on FHIR is the logical compromise: healthcare-specific enough to matter, but standardized enough to reuse. Nobody Asked Judy Another friend asked “I thought they had to go to each health system, or did they go direct to Epic and now health systems opt in?” Given the trust paradigms in healthcare, this functionally cannot be Epic hoovering up all the data for OpenAI and shoving ChatGPT in their customers’ faces (or they would revolt). However, I do believe the aforementioned terrible coverage by TechCrunch and other outlets is probably responsible for that question, given the 325 million reference. When using FHIR as a business associate to an Epic customer, there is no EHR gatekeeping to speak of, as that isn’t how fhir.epic.com works: You register an app You pick your APIs You test against the sandbox APIs You list as “Ready for Production” Hospitals pick your app You test and go live with them Bluntly, nobody had to say yes or no in Verona (nor were they given the chance). Vendor Services (their next developer tier up that I doubt OpenAI is using quite yet in this initial release) certainly has contractual paperwork that some resent, but even there, the twin pressures of mounting antitrust and information blocking make outright gatekeeping increasingly fraught. My friend’s sentiment is, to me, representative of a broader industry neurosis, perhaps a sort of scar tissue of prior eras: people assume the gate is still there and never actually try the door. There are certainly other ways Epic (and any EHR) can put its thumb on the scale, but they are not so dumb as to stand in front of a federally mandated API and play bouncer at this exact moment in time. So I think they can and probably should go deeper, as this release is at best parity and at worst behind vertical-specific competition. OpenEvidence did a basic SMART launch with Sutter Health in February, allowing for more convenient evidence search by providers. They then add patient-context (the equivalent SMART on FHIR flow to what we see here) when Cedars-Sinai went enterprise-wide in May. UpToDate has four distinct applications across deeper workflows like patient engagement listed in Epic Showroom and announced a partnership with Epic to power Art at UGM Abridge and other ambient scribes have invested deeply into the deepest bidirectional clinical copilot workflow with integrations well beyond SMART on FHIR. In that light, the “Who is OpenAI primarily targeting here?” is clear. This release brings them into striking distance of OpenEvidence, but not the others quite yet. They are the only one of the three you can reach without building something truly Epic-specific. When will they go further? Competition is a great motivator to overcome the horizontal demons and start building things that can’t be reused: not across industries, not across EHRs, maybe not past the customer you built them for. That’s the price of actually verticalizing. The question is if and when OpenAI will be willing to pay it. Month in Review Here is the monthly review. As a reminder, this is a regular round-up of the month’s posts and other content to surface things you may have missed across regulation, litigation, interoperability, and beyond. AI assistance is used in these bullet summaries so I can focus on articles. Articles Published: None this month Video Content: The Information Exchange: Standards-based Thruple Edition (Aug 14): Back to school for us too, with Brad reporting in from the CMS Health Tech Ecosystem’s one year anniversary in DC. We get into the January CMS-0057 deadline, the fall rulemaking reading list, and why enrollment still keeps most apps off FHIR. The Information Exchange: Epic Dúnadan Edition (Aug 25): A UGM roundup with Ryan Brickner joining for the first time to check our takes against what the building actually thinks. Rangers, Ergo sitting on top of EHI, and a down-market lineup that needs some cuts. Regulatory: Stacked Deck, Bad Hand (Aug 05): ONC’s website refresh took the entire HIT Policy Committee record with it, so I rebuilt the archive and went looking for the regulatory capture story everyone assumes is buried in there. Stacking the deck and winning the hand turn out to be very different things. The Sixth Generation of Patient Access (Aug 19): A quick catalog of the five generations of patient access we’ve layered on since HIPAA, and the two candidates now competing to be the sixth. One is planned. The other is the market routing around the plan entirely. Court cases: Three Cases Walk Into a Docket (Aug 06): Two surprise settlements cleared the board in a single week, and then Judge Maddox dropped ninety-four pages on Vyne v. Henry Schein. The sleeper is a DMCA holding that makes direct-to-database a considerably riskier business model. Epic v. Health Gorilla: Into the MDL (Aug 10): Nine class actions are headed to Miami, and the Panel signaled it wants to bring the case that spawned them along too. That would leave Epic arguing the requests were obviously fraudulent in one courtroom and unknowable in the other. Amazon v. Perplexity: Agents Are Legalized! (Aug 11): The Ninth Circuit vacated the injunction against Comet, holding that the user is the one accessing the servers rather than the company that built the agent. A real win for agentic access, and a much narrower one than the headline suggests. Veeva v. Epic: Come At Me, Bro (Aug 26): Epic’s response brief wants the dismissal affirmed and, unusually, wants the opinion published as precedent. Buried in it is Epic’s own description of what its non-competes actually prohibit, which current and former employees should read closely. EHRs: The Contract Epic Would Never Sign Today (Aug 04): A 1999 SEC exhibit catches Epic licensing nearly its entire product line, Tapestry included, to the company that became TriZetto. The marketing services menu attached to it is the part that will make you blink. Forecast from Verona (Aug 07): The Epic Almanac makes one argument six different ways: the AI is only as good as the networks behind it. Emmie headlines, Art’s context stack is the most ambitious part, and Penny finally gets an autonomous coding date on the calendar. Works With Epic MyChart (Aug 17): Epic’s first new Showroom category since the death of Workshop certifies hardware instead of software, badge on the box and all. Made for iPhone, but for blood pressure cuffs, and rough news for anyone selling the RPM stack sitting in between. UGM Hot Takes 2026 (Aug 20): Everyone else covered the AI announcements, so I went after Savvy deleting the payment gateway, Rangers as Boost with the timer removed, and a down-market lineup with too many entries. Plus the Health Grid tidbits I cannot help myself on. MyChart Central Grows Up (Aug 24): Device data and Emmie turn Epic’s identity hub into a full consumer platform, which is both a logical answer to ChatGPT and a bit of a mistake. It also happens to be the best scraping target Epic has ever shipped. Industry Analysis: The Wrong Yardstick (Aug 12): Vertical software keeps getting judged against Superhuman and Notion, which is the wrong bar entirely. Your user is comparing your product to a whiteboard and forty phone calls before lunch. Primitives vs. Abstractions (Aug 27): Developers want building blocks, systems of record prefer to hand out business logic, and both sides have a real case. There’s no test from the outside that separates the engineering reason from the competitive one, which is why this keeps ending up in court. Cross-industry Comparisons: The Two Kinds of Platform Power (Aug 18): Attention power and record power are different problems that keep getting handed the same regulatory toolkit. Congress’s latest swing at Big Tech shows both what’s possible and where it falls apart. The Dogs of (Platform) War (Aug 21): A CourtListener alert turned up a property management fight with healthcare’s exact shape and none of the Cures Act. Shell prospects, ghost accounts, a notetaker bot that came back to haunt someone, and a lawyer arguing both sides of the same theory in two states. Fractals All the Way Down (Aug 31): Yardi dominates property management right up until you zoom into one segment, where AppFolio owns it outright and Yardi doesn’t appear at all. Where you draw the line around a B2B software market is about to decide an awful lot of cases. Other News: If Judy Had the Courage (Aug 13): A short eulogy for the era when software was allowed to look insane: WinAMP, bold colors, and everything the grey chatbot era has taken from us. External Media: Portland Monthly Health Tech Meetup: Erin O’Brien channeled my own feelings - maybe it’s just because it’s August and beautiful, but the monthly edition of the PDX Health community meetup was a ripper. Make sure to reach out if interested to join for the next one. STAT’s Coverage of Epic This Month: Brittany Trang of STAT did a fantastic job of breaking the FTC investigation that’s been lurking, as well as UGM related coverage, so I had to give her her wish of a meme. Fall Conferences: I’m pumped to be kicking off my fall conference season in NYC at Nabla Accelerate next month, which Chrissy provided the link to apply for. Here’s the rest of my schedule in case you want to meet up: Commonwell (Redwood Shores, CA): Oct 13-14 Open@Epic (Madison, WI): Oct 21-22 eHealthExchange (Austin, TX): Oct 27 Sequoia Project (Austin, TX): Oct 28-29 HLTH (Vegas): Nov 15-18 RSNA (Chicago): Nov 29-Dec 3 Posts I Liked: HTI-6 Should Unbundle API Certification: Josh Mandel makes the case that HTI-6 should split (g)(10) into separate authorization and data certifications, so a PACS or a genomics platform can certify only the role it actually performs. Imaging is the urgent example, but the structure solves a much bigger problem. On implementing ePrior Auth with Epic: Scott Rossignol’s field notes from a live ePrior Auth build on Epic, including the two app registrations nobody warns you about and the CPT mapping problem waiting at the end. CMS-0057 implementations are going to be such a beast. Healthcare point solutions are starting to look a lot like streaming services: Spencer Dorn runs the cable-to-streaming arc against health IT and lands squarely on the bundling half of the cycle. Bundling can be good! It can also be bad! Life is nuanced. Health API Guy is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
Jennifer Aniston’s boyfriend Jim Curtis reveals how the couple resolves fights in the ‘honeymoon phase’ stage
Jennifer Aniston’s boyfriend, hypnotherapist Jim Curtis, is revealing how the couple resolves conflicts while navigating the ‘honeymoon phase’ of their relationship.
Hubble Solves Merger Mystery From Milky Way’s Early Years
New Hubble data shows definitive evidence of a dwarf galaxy merging with the young Milky Way in the earliest phases of its evolution.
Business Restructuring Review Vol. 25 No. 4 July-August 2026
In This Issue New York Bankruptcy Court: Premature Allegations of Creditor Mistreatment Insufficient to Deny Chapter 15 Recognition of Foreign Restructuring Proceeding In In re ARD Finance, S.A., No. 25-12794 (MG), 2026 WL 817458 (Bankr. S.D.N.Y. Mar. 25, 2026), the U.S. Bankruptcy Court for the Southern District of New York was presented with a petition seeking chapter 15 recognition of Luxembourg's recently enacted bankruptcy law governing judicial reorganization proceedings. The court granted the petition, turning aside challenges to recognition voiced by a creditor group arguing that recognition should be denied based upon allegations of unfairness to creditors in the Luxembourg proceeding that would make recognition manifestly contrary to U.S. public policy. According to the bankruptcy court, recognition was warranted because: (i) the rules and procedures governing the proceeding under Luxembourg law were fundamentally fair; (ii) the petition otherwise satisfied chapter 15's recognition requirements; and (iii) the creditor group's allegations were premature, given the fact that the Luxembourg court presiding over the debtor's restructuring proceeding had not confirmed a restructuring plan, and all creditors had the right to participate fully and voice their objections in the proceeding (including the right to appeal an order approving a plan). [read more …] Florida Bankruptcy Court Examines Scope of Discovery in Chapter 15 Cases In In re Banco Master, S.A., No. 25-24568-SMG, 2026 WL 931729 (Bankr. S.D. Fla. Apr. 6, 2026), the U.S. Bankruptcy Court for the Southern District of Florida granted in part and denied in part post-recognition motions filed by an insider of a foreign debtor seeking to bar or limit discovery sought by the debtor's foreign representative concerning allegedly voidable transfers involving the debtors' U.S. real property. According to the court: (i) although chapter 15 includes its own discovery provisions among the relief that may be granted to a foreign representative, the expansive discovery available in cases under other chapters of the Bankruptcy Code is also available in chapter 15 cases; (ii) the discovery sought by the foreign representative was permissible; (iii) discovery regarding matters that were the subject of a pending adversary proceeding had to be undertaken under the more restrictive rules applicable to such proceedings; and (iv) a discovery request would be barred to the extent that it sought production of documents or testimony from a subpoenaed entity that exceeded the geographic limitations specified in such rules. [read more …] Delaware District Court Affirms Chapter 15 Recognition Order Enforcing Nonconsensual Third-Party Releases In U.S. Int'l Dev. Fin. Corp. v. Credito Real S.A.B. de C.V. SOFOM, E.N.R. (In re Credito Real S.A.B. de C.V. SOFOM, E.N.R.), 677 B.R. 192 (D. Del. 2026), appeal filed, No. 26-2356 (3d Cir. June 5, 2026), the U.S. District Court for the District of Delaware affirmed a bankruptcy court order granting chapter 15 recognition to a Mexican "concurso mercantile" proceeding and enforcing nonconsensual third-party releases approved by the Mexican court. Agreeing with the bankruptcy court that the releases were not manifestly contrary to U.S. public policy, the district court concluded: "It is well settled that U.S. bankruptcy courts can give effect to foreign orders in recognized foreign proceedings pursuant to the authority granted in Chapter 15, even when those orders contain relief unavailable under U.S. law. [The appellant's] arguments misconstrue the Supreme Court's narrow holding in Purdue, applicable in Chapter 11 cases, as well as the statutory framework of Chapter 15 and its core policy objectives. Accordingly, I will affirm the Enforcement Order." The ruling has been appealed to the U.S. Court of Appeals for the Third Circuit. [read more …] Fifth Circuit: Bankruptcy Court, Not State Court, Had Jurisdiction to Allow or Disallow Administrative Expense Claim In Storey Minerals Ltd. v. EP Energy E&P Co., LP (Matter of EP Energy E&P Co., LP), 169 F.4th 609 (5th Cir. 2026), the U.S. Court of Appeals for the Fifth Circuit affirmed lower courts' rulings disallowing a creditor's administrative expense claim. It also rejected the creditor's argument that, because the claims were predicated on state law, a state court should adjudicate the merits of the state law causes of action before the bankruptcy court could allow or disallow the claim as an administrative expense. According to the Fifth Circuit, even though the causes of action were based on state law, the bankruptcy court had jurisdiction to determine whether the creditor's claims should be conferred with administrative expense priority in the debtors' chapter 11 case. [read more …] New York Bankruptcy Court: Dismissal of Involuntary Chapter 11 Case Filed Prior to Commencement of Foreign Restructuring Proceeding Unwarranted In In re Xinyuan Real Estate Co. Ltd., No. 25-10745 (PB), 2026 WL 592250 (Bankr. S.D.N.Y. Mar. 3. 2026), the U.S. Bankruptcy Court for the Southern District of New York considered the bona fides of an involuntary chapter 11 petition filed by certain holders of U.S. dollar-denominated notes against a holding company for a group of Chinese property development companies that filed a restructuring proceeding in the Cayman Islands after the noteholders filed the involuntary chapter 11 petition. The court denied the debtor's motion to dismiss the chapter 11 case. Given the timing of the filing of the Cayman Islands restructuring proceeding, the absence of any progress in the proceeding for seven months, the debtor's need to restructure notes governed by U.S. law, and the debtor's lack of any meaningful contacts to the Cayman Islands, dismissal of the chapter 11 case was unwarranted under the applicable provision of the Bankruptcy Code, international comity, or the doctrine of forum non conveniens. [read more …] Bankruptcy Court Evaluates Trustee's Authority to Sell Avoidance Actions and Right of Target Defendants to Object In In re Law Enf't Officers Sec. Union, No. 24-70277-JAD, 2026 WL 560452 (Bankr. W.D. Pa. Feb. 27, 2026), a chapter 7 trustee sought court approval to sell certain avoidance actions to a creditor of the debtor's estate. Potential targets of the subject avoidance actions objected, arguing that such claims were nontransferable powers of the trustee rather than saleable estate property and urging the court to approve their competing settlement with the trustee. The U.S. Bankruptcy Court for the Western District of Pennsylvania disagreed with the potential defendants, holding that they lacked standing to object to the proposed sale, that avoidance actions are indeed estate property, and that the sale—rather than the settlement—best served the estate's interests. [read more …] U.S. Supreme Court Bankruptcy Roundup in Brief In Keathley v. Buddy Ayers Construction Inc., No. 25-6, 2026 WL 1686028 (U.S. June 11, 2026), the U.S. Supreme Court overturned a Fifth Circuit decision judicially estopping a chapter 13 debtor from asserting a personal injury claim against a construction company because the debtor failed to disclose the claim during his bankruptcy case. In so ruling, the Court held that "[t]he Fifth Circuit erred by artificially narrowing its inquiry to whether the debtor had knowledge of the underlying facts or a potential motive to conceal the claim." It represents the first time that the Court has applied judicial estoppel in the bankruptcy context, although it has suggested in other contexts that it may be inappropriate where an inconsistent legal position resulted from "inadvertence or mistake." Also in June, the Court denied petitions for certiorari in a few notable bankruptcy cases. [read more …] Newsworthy Heather Lennox (Cleveland/New York) (Star Individual), Bruce Bennett (Los Angeles) (Senior Statesperson), Kevyn D. Orr (Washington) (Eminent Practitioner), Gregory M. Gordon (Dallas) (Band 1), Carl E. Black (Cleveland), Corinne Ball (New York) (Senior Statesperson), Brad B. Erens (Chicago), Jeffrey B. Ellman (Atlanta), T. Daniel Reynolds (Cleveland), and Dan T. Moss (Washington/New York) were recognized as leading lawyers in the practice area Bankruptcy/Restructuring in the 2026 edition of Chambers USA: The World's Leading Lawyers for Business. The 2026 edition of Lawdragon 500 Leading Bankruptcy and Restructuring Lawyers ranked the following lawyers: Corinne Ball (New York) (Hall of Fame), Bruce Bennett (Los Angeles), Carl E. Black (Cleveland), Jeffrey B. Ellman (Atlanta), Brad B. Erens (Chicago), Gregory M. Gordon (Dallas), Heather Lennox (Cleveland/New York), Joshua M. Mester (Los Angeles), and Kevyn D. Orr (Washington). Fabienne Beuzit (Paris) and Jasper Berkenbosch (Amsterdam) were among the "Leading Individuals" ranked in the 2026 edition of The Legal 500 EMEA guide in the field of Restructuring and Insolvency or Insolvency. Rodolphe Carrière (Paris) was named a "Next Generation Partner" in the practice area Insolvency. Sid Pepels (Amsterdam) was selected by Global Restructuring Review's 40 under 40 2026. He was identified as a Rising Star within the global cross-border restructuring community. Global Restructuring Review is a leading digital subscription service, news outlet, and information platform dedicated exclusively to cross-border insolvency and corporate restructuring law. Fabienne Beuzit (Paris), Rodolphe Carrière (Paris), and Isabelle Maury (Paris) were recognized in the 2027 edition of The Best Lawyers in France™ in the practice area Insolvency and Reorganization Law. An article written by Corinne Ball (New York) titled "Comity and Fairness are Critical to Granting Additional Assistance under Chapter 15: A Canadian Reverse Vesting Order and Related Releases in Proceedings Involving Canadian and U.S.-Affiliated Companies Are Approved" was published in the June 24, 2026, edition of the New York Law Journal. An article written by Caitlin K. Cahow (Detroit) titled "New York Bankruptcy Court Weighs In on Adequate Assurance of Future Performance under Assigned Leases and Chapter 11 Plan Exculpation Provisions" was published on June 8, 2026, in Lexis Practical Guidance. An article written by Trisha L. Mowbray (Real Estate; Chicago) and Ryan Sims (Washington) titled "Chapter 11 Plan that Abridged Non-Debtor Lessee's Rights to Remain in Possession After Rejection Unconfirmable as Having Been Proposed in Bad Faith" was published on June 16, 2026, in the Harvard Law School Bankruptcy Roundtable. An article written by Dan T. Moss (Washington/New York), Corinne Ball (New York), Isel M. Perez (Miami), and David S. Torborg (Washington) titled "Texas Bankruptcy Court Adopts Barnet Rule Requiring Foreign Debtor to Have U.S. Assets to Be Eligible for Chapter 15 Relief" was published on June 10, 2026, in Lexis Practical Guidance. An article written by Daniel J. Merrett (Atlanta) and Nathaniel Parr (Atlanta) titled "Southern District of Texas Clarifies Post-Purdue Course for Consensual Third-Party Releases and Gatekeeping Provisions" was published on June 11, 2026, in Lexis Practical Guidance. An article written by Corinne Ball (New York) titled "LMEs, Sophisticated Investors and Equitable Mootness: The Fifth and Third Circuits Warn Against Testing the Limits of Chapter 11" was published in the June 2026 issue of the American Bankruptcy Institute Journal. Nicholas J. Morin (New York) was quoted in an article titled "Serta Ruling Offers Damages Road Map in Lender-on-Lender Disputes," published by Bloomberg Law on July 7, 2026. The article discussed U.S. Bankruptcy Judge Christopher Lopez's July 7, 2026, ruling that participating lenders in Serta Simmons Bedding's 2020 non-pro rata uptier exchange breached the credit agreement's ratable-sharing provision, and awarding excluded lenders more than $261 million in damages. The opinion resolves six years of litigation related to Serta's 2020 transaction, where it raised $200 million in new financing and exchanged $1.2 billion of term loans for $875 million in superpriority debt. Judge Lopez found that the debt-for-debt exchange constituted a "payment" under the credit agreement, requiring proportional sharing among lenders, and dismissed various defenses raised by the participating lenders. The case is Serta Simmons Bedding LLC v. AG Centre Street Partnership (In re Serta Simmons Bedding LLC), 2026 WL 1968535 (Bankr. S.D. Tex. Jul. 7, 2026). The New York Law Journal has recognized Andrew M. Butler (New York) as a 2026 "Rising Star" in Restructuring/Bankruptcy as part of the New York Legal Awards. The Rising Star category recognizes New York's most promising lawyers age 40 and under who have distinguished themselves through exceptional legal work, leadership, and contributions to the profession. Lawyer Spotlight: Daniel J. Merrett Dan Merrett, a partner in the Atlanta Office, has spent nearly 20 years representing all manner of stakeholders in complex corporate restructurings and chapter 11 reorganizations. His practice extends to related transactions and disputes involving acquisitions; divestitures; credit facilities; securities; environmental obligations; and vendor, employee, and governance matters. Dan has substantial experience managing mass tort liabilities, including the restructurings and related chapter 11 cases of affiliates of Georgia Pacific and Johnson & Johnson, implemented to resolve asbestos and talc liabilities. He also represents key parties in energy and infrastructure matters, including facility owners, EPC contractors, and joint-venture parties. Dan was a key player in the restructuring teams in the historic bankruptcies of the City of Detroit and Chrysler. His other significant representations in chapter 11 cases include AFA Foods, Alpha Natural Resources, Dana Corporation, M&G Chemicals, McDermott International, Monster/CareerBuilder, Transtar Industries, and Westinghouse. He is licensed in both the United States and England & Wales and recognized in restructuring by Chambers USA and Best Lawyers.
Vikings Get Intriguing Message Involving Buccaneers’ Baker Mayfield
The Minnesota Vikings are having a QB battle between Kyler Murray and J.J. McCarthy to determine their starter for the 2026 NFL season. In a perfect world, one of McCarthy or Murray emerges and solves the Vikings’ issue under center for the foreseeable future.Nonetheless, there’s also the possibility that neither is the answer after having […] The post Vikings Get Intriguing Message Involving Buccaneers’ Baker Mayfield appeared first on HEAVY.
The Science Behind the AI Panic Is Shakier Than You Think
A column by Sascha Lobo Is AI making us dumb? So asked DER SPIEGEL on its cover a while ago. After a few weeks of recovery and a therapeutic intervention with the help of my AI, I feel able to respond. That’s a bit unfair, of course; the article itself is more nuanced than the loud cover, the image of a schoolkid with dull prompt questions, or the subtitle: “AI is conquering the schools, and educators fear a disaster.” The short answer to “Is AI making us dumb?” is: no. The long answer is more interesting, and even carries a preliminary glimmer of the spectacular. Unfortunately, it requires a detour into the sphere of artificial intelligence, into the mogul-field terrain of technology assessment, the attention economy, and the destructive virus of cultural pessimism. Along with narrowing the scope to AI’s effects on education and work rather than on intelligence. Because the honest version of the question would be: Does AI help us learn and work, or not? Generative AI, which set off the still-ongoing hype with ChatGPT, has only existed in relevant distribution since late 2022, early 2023. For a technology-driven transformation of people and society, that is extremely short. For that reason alone, research is still in its infancy. And technology assessment is not a fast discipline anyway. Prominent voices from Elizabeth Eisenstein to RAND to Tom Wheeler say we still cannot conclusively judge the consequences of the printing press. Its invention is a mere 580 years back, and some scholars would rather not circulate assessments that might have to be retracted in two or three hundred years. We’re Going Through Growing Pains A phenomenon that already caused upheaval in social media research makes serious assessment of AI’s consequences even harder: the “moving target” problem of LLM-ology, as the linguist Sean Trott called it in 2025. AI develops so quickly and so unpredictably that researchers often end up studying snapshots of the past. There are concepts, from morphological analysis to anticipatory governance, for keeping research, planning, and regulation halfway meaningful anyway. But even with those, universally valid statements are rare. DER SPIEGEL - The German View is a reader-supported publication. To receive new posts and support our work, consider becoming a free or paid subscriber. Subscribe We should therefore treat findings about the interplay between humans and AI as far more procedural and situational. Unfortunately, this challenge comes at the worst possible time. We are going through growing pains: AI’s everyday impact has grown very large very fast, and with it the longing for guidance. Annoyingly, the body of solid knowledge has not exploded along with it. Experts cannot be moved to broad consensus on even banal statements about AI. Sascha Lobo, born in 1975, is an author and strategy consultant focusing on the internet and digital technologies. Together with Jule Lobo, he explores the debates of the day in the podcast “Feel the News – Was Deutschland bewegt” (”What Moves Germany”). Nvidia CEO Jensen Huang says software developers are dying out. Bill Gates considers coders one of only three professions that will survive the AI tsunami. Top tech economists find virtually irrefutable arguments both for and against an AI bubble. The same naturally applies to the structurally youth-hostile debate over whether AI is good or bad for young people. The gap between the demand for insight and the supply of solid knowledge creates an orientation vacuum. This vacuum of AI cluelessness is filled, as the attention economy described by Georg Franck in 1998 would have it, with half-knowledge (funnily enough, often AI-generated), marketing, and self-marketing. After all, infinite money is at stake, along with academia’s best current shot at global fame. But this iridescent froth of interpretation operates more by the algorithmic principles of the digital public sphere than by seriously earned insight. That is why dramatized, fear-feeding claims about AI are so promising. It tempts parts of academia into distorted drivel, and parts of the media then sensationalize the published drivel once more. Was the Research Aimed at a Desired Result? How badly this can influence academia and public perception is demonstrated by one of the most-discussed studies on AI’s effects: “Your Brain on ChatGPT.” The MIT study by Nataliya Kosmyna also gets plenty of space in the SPIEGEL cover story. What was measured and interpreted: lower brain activity in people who write with AI assistance, compared to people who only google or write without any tools. As is common with preprints, the study has not yet been peer-reviewed, and it contains substantial weaknesses that experts have sharply criticized. The first round had 54 participants in three groups, the second only 18, who reportedly also came from MIT’s own orbit. There was no preregistration (committing in advance to what you want to find out with which data). In their analysis, Stanković et al. even discovered an opposite effect that the study does not further explain. Some measurement data has not (yet) been published. And the EEG analysis method used is considered too imprecise to support such far-reaching conclusions. The biggest criticism, though, is the suspicion of an activism-driven study. In an interview with Time, lead author Kosmyna said she published the study immediately, rather than after full peer review, because she feared politicians might otherwise decide to put ChatGPT in kindergartens. She considers that absolutely harmful. It is legitimate to hold such a view. It just seems unscientific to approach a study with it, and then to design the setup so that the chance of a fitting desired result remains as high as possible. Ideologies Collide It is not easy to separate genuine AI insights from studies that trivialize and weaken well-founded AI criticism. The same goes for the opposing, AI-enthusiastic narratives, because the pro-AI side works against it with billions in resources. Ideologies collide, fed by egos, PR strategies, moral posturing, and once-in-a-lifetime opportunities. Doomsday marketing makes the search even harder: AI companies can profit from warnings about the dangers of AI, whether through the notoriety of apocalypse narratives or because, in some target groups, danger translates into power. Some seemingly negative findings are therefore quite welcome in the AI industry. If you try to get at the findings presumably less influenced by interest groups, the picture in education seems relatively clear: AI can improve educational outcomes when the right AI is used the right way, namely pedagogically. Simply dumping an AI chatbot into a classroom, by contrast, accomplishes little. Huge surprise. But something else is also obvious: whether they are allowed to or not, kids use AI for school, which is why the controlled integration of AI tools into education is, in the medium term, entirely without alternative. In the world of work, the landscape of findings is more complex and requires more differentiation. A series of serious studies points to an AI effect that suits neither the alarmists, regulation fetishists, and AI opponents, nor the trillion-dollar corporations with their armada of paid scientists, PR professionals, and ecosystems: working with AI helps the inexperienced (at least for now) considerably more than it helps the pros, in certain fields of work, and provided they know how to use it correctly. Missing Domain Knowledge Among the experienced, the professionals, and the high flyers, by contrast, despite frequent time savings, partially negative effects and new problems are emerging. Take the jagged frontier problem: AI solves task A brilliantly and fails completely at task B, even though both look similar even to professionals. Or the verification-cost problem, in which AI’s greater productivity gets eaten up by the enormous effort of checking its output. Or the illusion of competence, because AI makes new domains seem easily penetrable, until you painfully discover that deep domain knowledge is missing. Taken as a whole, the effects of working with AI do lean positive. But the promise that AI works as a turbocharger for everyone and boosts practically everything simply refuses to materialize. The AI magic the world has been feeling since ChatGPT arrived in late 2022 has so far barely shown up in most companies’ numbers. The consulting firm McKinsey has coined a term for this, the “gen AI paradox,” and believes that work processes and corporate structures would have to be rebuilt quite fundamentally to realize AI’s benefits at scale. Reuters just reported that only 3.3 percent of Microsoft’s customers have subscribed to the AI package Copilot. That may be down to the product; in other areas we continue to see soaring successes and new AI triumphs. But after the first quarter of 2026, disillusionment is the word for all too many AI projects at traditional companies: because the promised revolution of AI agents has so far failed to arrive or been postponed, and because of the leveling effect that many of the studies cited here suggest. Against Inequality The societal effects, on the other hand, appear rather encouraging. Many previous technologies operated on the Matthew principle, named for the Gospel verse about giving to those who already have: they tended to reward the more competent and more privileged. AI, however, seems more often to have an equalizing effect once a threshold of access and education is crossed. Some anecdotal insights point in this direction, for example, how an unemployed man in Leipzig successfully defended himself in court in 2025 against fraud accusations from Germany’s federal employment agency — without a lawyer, armed only with ChatGPT. The AI made mistakes and cited invented court rulings, but in the end the man walked away unpunished. And a key capability of artificial intelligence is its capacity to learn: set up correctly and fed with data, it can keep getting better. It is a question of time, or more precisely of AI innovations and training data, until even free AI chatbots write better legal briefs than law graduates with perfect exam scores. Whether that will make anyone dumb is something the world’s press will surely inform us of in due time. Subscribe Leave a comment
Multi-agency safely resolves mental health crisis on I-95
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Every so often a story comes along that is so brazen, so cleanly emblematic of the moment we are living through, that staying quiet about it feels like a kind of complicity unto itself. Monday’s announcement by the Department of Justice that the Acting Attorney General has unilaterally created a $1.776 billion “Anti-Weaponization Fund” to compensate so-called “victims of lawfare” is one of those stories. And the reason I want to write about it here, in a newsletter ostensibly devoted to the Supreme Court and the law and politics surrounding it, is that I’m increasingly worried that we’re asking the wrong institution to save us from one of the most offensive, alarming, and anti-constitutional things we’ve seen from any president in American history. As I explain below the fold, the Anti-Weaponization Fund is not principally a legal problem awaiting a judicial fix. It is a shockingly egregious political abuse—the President suing his own government, purporting to settle with himself, and routing nearly $2 billion from the Treasury to his own supporters as a not-so-subtle (and not-so-formal) reward, if not an incentive, for political violence. And the Constitution’s answer to political abuses of this kind and magnitude is a political remedy, not a legal one. In his majority opinion in NFIB v. Sebelius (the Affordable Care Act case from 2012), Chief Justice Roberts defended the Court’s endorsement of Congress’s power to adopt the individual mandate by noting that it is “not our job to protect the people from the consequences of their political choices.” As much of a judicial supremacist as I am, that sentiment is, for better or worse, an entirely correct (and, in the long term, normatively desirable) institutional assessment. One can believe in substantial judicial power without believing that literally every political dispute in our country can and should be resolved by unelected judges. The real upshot of this latest headline (among so, so many other similar headlines) is that it is past time to reinvigorate impeachment—not because conviction is realistic in this Senate, or even because impeachment itself is feasible in this House, but because forcing every member of Congress to vote on the record whether this brazen, corrosive, and affirmatively dangerous corruption is impeachable is itself a point worth fighting for (and fighting with our friends over). Assuming the courts will save us absolves our political leaders of both responsibility and accountability for allowing this kind of mischief to continue, and it absolves all of us of our responsibility to refuse to tolerate those who would just as quickly shrug their shoulders and move on. For those who aren’t paid subscribers, we’ll be back (no later than) Monday with our continuing coverage of the Supreme Court. For those who are, please read on.
New MatterChat Model Helps AI to ‘See’ the Language of Science
From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has succeeded by mastering one domain: text. However, this leaves a major blind spot in the physical sciences, where models depend on the high-resolution, three-dimensional data of the physical world, like the intricate lattice of atoms in a crystal. Delivering on the promise of using AI for science requires teaching these data-driven text models to seamlessly “talk to” physics-based models. Now, a new AI framework from Lawrence Berkeley National Laboratory (Berkeley Lab), called MatterChat, solves this problem by creating a specialized “bridge.” It connects the conversational power of a Large Language Model (LLM) with a physics-based AI that models “interatomic potentials”: the complex physical forces between atoms. The resulting system already significantly outperforms general-purpose AI tools like GPT-4 at predicting material properties, and the team hopes it can accelerate scientific discovery by serving as a robust research partner that provides grounded insights and generates step-by-step instructions for synthesizing novel materials. A paper describing this work was recently published in Nature Machine Intelligence. “Traditional simulations can provide the physical rigor required for materials science, yet their computational cost remains prohibitive for high-throughput screening. Conversely, while LLMs excel at rapid knowledge synthesis, they inherently lack the ‘structural vision’ to interpret materials directly from their underlying atomic coordinates,” said Yingheng Tang, a postdoctoral researcher in Berkeley Lab’s Applied Math and Computational Research Division (AMCR) and lead author on the paper. “MatterChat was built to solve this dilemma, empowering LLMs with a structural ‘vision’ that allows researchers to leverage their full potential for solving complex, real-world materials challenges.” Empowering language models to solve complex challenges in materials science To build MatterChat, the Berkeley Lab team drew inspiration from technologies like Vision Question Answering (VQA) and Text-to-Image (T2I) generation. In these tasks, AI must translate high-level text concepts into visual images, or vice versa. Doing so requires developers to build tools that “bridge” two fundamentally different forms of data. The researchers adapted this concept to the physical sciences. With MatterChat, they created a “bridge model” that successfully connects an LLM’s general knowledge with the deep understanding of the atomic-scale world encoded in scientific interatomic potentials. Until now, researchers using LLMs to solve materials problems usually had to feed them raw data files as if they were just strings of text. It’s like asking an AI to understand a complex 3D engine based only on a parts list: the LLM can read the names, but it can’t “see” how the atoms fit together in space. MatterChat solves this by training a specialized AI bridge model, pre-trained on millions of crystal structures and an LLM, to align the LLM’s representation of the world with the interatomic potential’s representation of the world. The bridge model can translate physical insights into a format the LLM can actually understand. By giving the LLM these “scientific eyes”— a scientific “inductive bias” in the terminology of AI — the Berkeley Lab team has transformed it into a robust research tool capable of providing grounded scientific insights into complex materials challenges, such as predicting thermal stability or analyzing electronic band gaps. “We think of atoms as living in a physical space, but from a machine learning perspective, they are just vectors living in some very non-trivially structured manifold in a high-dimensional Euclidean space; and, of course, the same is true for the sentences and paragraphs that we use to express our ideas about those atoms,” said co-author Michael Mahoney, Berkeley Lab’s Scientific Data Division (SDD) AI Initiative Research Lead. “The bridge model basically gets those two structures to ‘talk with’ each other.” As a proof-of-concept of this general approach, the team trained their bridge model on a dataset curated by pairing nearly 143,000 stable atomic structures from the Materials Project with their corresponding physical properties. This training data was automatically assembled using the Materials Project’s API and deliberately enriched with properties fundamental to microelectronics design — like formation energy and bandgap — allowing MatterChat to learn the complex patterns connecting a material’s atomic blueprint to its functional performance. To validate their model, the researchers benchmarked MatterChat against a suite of other AI systems, from general-purpose LLMs to other specialized scientific AI methods. The results show that MatterChat consistently outperformed its competitors across a range of tasks. The model was more accurate in classifying material types and demonstrated superior precision in predicting numerical properties. For example, it excelled at predicting a material’s bandgap, a property critical for designing new electronics from high-capacity energy storage to next-generation computer chips. “Our design is significantly more efficient because we don’t have to build a massive AI model from the ground up,” said co-author Zhi (Jackie) Yao, a research scientist in Berkeley Lab’s AMCR. “Instead, we take two powerful, pre-trained models — a structural encoder for materials physics and an open-source LLM — and use them off-the-shelf. The only component we actually train is the lightweight ‘bridge model’ that translates between them. It’s the difference between building an entire car factory and simply designing a smart adapter that connects a world-class engine to a world-class navigation system. This approach is not only computationally efficient, but also makes the system modular, so we can easily upgrade components or adapt the bridge for other scientific domains in the future.” Crucially, this modular design highlights exactly how institutions like Berkeley Lab and the Department of Energy are carving out a highly valuable niche in the booming AI landscape. Rather than competing with Silicon Valley tech giants to build ever-larger language models from scratch, the lab is focusing on the specialized connective tissue that makes commercial AI useful for hardcore science. Because the bridge model approach underlying MatterChat is forward-compatible, it is perfectly positioned to leverage these parallel tracks of innovation. As Mahoney pointed out, “We expect that industry will continue to develop improved LLMs, and we expect domain scientists and facilities will continue to generate new data. An important part of scientific machine learning is not simply to solve problems on today’s data, but instead to develop general methods that will be forward-compatible with orders of magnitude more data, whether from scientific domains or from LLMs.” According to Yao, the MatterChat project, which was initially developed and enhanced with funding from a Berkeley Lab Laboratory Directed Research & Development (LDRD) Program, will now expand its capabilities. In a collaboration with Fermilab, MatterChat is already contributing to a U.S. Department of Energy Genesis Mission project — called Accelerating eXtreme Environment Specs-to-Silicon (AXESS) — that aims to speed up the development of next-generation, high-speed, radiation-hardened detectors for challenging particle physics experiments by using advanced 3D integrated circuits (chiplets) and AI-driven data analysis. In addition to the LDRD support, the team also credits supercomputing resources at the National Energy Research Scientific Computing Center (NERSC), located at Berkeley Lab, with MatterChat’s success. “We are incredibly grateful to NERSC; this research simply would not have happened without access to the Perlmutter supercomputer through their AI for Science program,” said Tang. Wenbin Xu, a NERSC postdoctoral fellow at the time, was also a major co-author of the work, as was Benjamin Erichson, a research scientist in Berkeley Lab’s SDD, highlighting the benefits of AMCR-SDD collaboration on AI for science. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
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Pebble's founder introduces a $75 AI smart ring for recording brief notes with a press of a button
After rebooting the Pebble smartwatch, founder Eric Migicovsky is expanding his company's device lineup with a new smart wearable: an AI-powered smart ring known as Index 01. Named for the finger where the ring is meant to be worn, the new $75 ring is not meant to be a competitor to the always-on, always-listening AI devices, like the AI pendant Friend, but instead offers a way to record quick notes and reminders with a press of a button on the ring's side. AI only comes into play via the open source, speech-to-text, and AI models that run locally on your smartphone, via the open source Pebble mobile app. That is, if the Ring's button is not being pressed, it's not recording. (And this is a press-and-hold gesture, too, which means you can't start the ring's recording and then let go to surreptitiously record a conversation.) You can wear the stainless steel ring while in the shower, washing hands, doing dishes, or in the rain, but you would have to take it off for other water-related activities, like swimming. At launch, it's water-resistant to 1 meter. The ring is also not a fitness tracker or sleep monitor. It doesn't record details about your heart rate or health. And it's not there to be your AI friend. "I'm not trying to build some AI assistant thing," Migicovsky told TechCrunch in an interview. "I build things that solve one main problem, and they solve it really well," he explains. "I think of as external memory for my brain...that's what this is. It's always with you." Plus, the ring has been designed to be highly reliable and privacy-preserving, he says, as all your thoughts are stored on your phone, not in the cloud. There is no subscription. Migicovsky has been wearing the ring for three months now and says he cannot imagine going back to a world where he doesn't always have a memory device with him. "The problem is that, during the day, I get ideas or I remember something, and if I don't write it down that second, I forget it," he says. The ring solves this problem, he adds, without becoming another device you need to charge. "The battery lasts for years," Migicovsky claims. Technically, the ring is said to support roughly 12 to 14 hours of recording. On average, the founder says he uses it 10-20 times per day to record 3-6 second thoughts. At that rate, he'll get about two years of usage. When the ring's battery dies, you can ship it back to the company for recycling. When using Index, you can record up to five minutes of audio, which can be saved to the ring and synced to your phone later. This makes sense for recording briefer, personal thoughts and notes, even when you don't have your phone handy, but it wouldn't work for recording a longer chat, like a presentation, meeting, or in-person interview of some kind. The ring also supports 99+ languages and has a bit of on-device memory, in case you're not in Bluetooth range of your device, where the recording is ultimately saved and transcribed. (The raw audio is retained, too, in case the speech-to-text is garbled due to loud background noise). If you own a Pebble smartwatch or one from another brand, your recorded thought can even appear on the watch's screen so you can verify it's correct. The ring works with Pebble's mobile app, which offers notes and reminders, but can optionally integrate with your phone's calendaring system, too, or other apps, like Notion. And the ring's software is open source, which makes it hackable by the community, the founder points out. Because of its open nature, the ring's button is already programmable. In addition to the press-and-hold gesture, you can program the ring to do other things with a single or double press, like play or pause your music or control the shutter on your phone's camera. You could use it to send a message through the universal chat app Beeper, which Migicovsky also created, or you could add your own voice actions via MCP. A new approach to hardware Migicovsky acknowledges that hardware can be difficult to get right -- as the previous exit of Pebble to Fitbit showed. (Fitbit, too, was later acquired by Google in 2021). "I didn't earn any money during Pebble -- we exited, but it was not a great exit," Migicovsky admits. This year, however, he decided to reboot the Pebble project after Google open sourced the PebbleOS, which opened up the door to new hardware. With his new company, Core Devices, Migicovsky plans to do things differently. Still, the founder doesn't regret his previous choices, he clarifies. "I wouldn't have gone back and changed anything. I loved what we built. I loved what we did. I love the company that we built, but it's not the only way to build a company," he told TechCrunch. " And, speaking as an ex-YC partner, there are -- there's a time and a place for building a venture-backed startup. Some companies are phenomenal when they raise money and build a big team, and I tried that...I think what I'm doing now is trying an alternative path, which is start from profitability," he says. The new company is a small team of five, self-funded, and focused on sustainability. So far, Core Devices has shipped the Pebble 2 Duo smartwatch with a black-and-white display. Its first run sold out, and the company is now preparing to ship the upgraded version, the Pebble Time 2. The newer device, which has seen 25,000 pre-orders, is a stainless steel watch with a larger, color e-ink screen. As for the Index 01, the ring's pre-order offer ends in March 2026. After that, the price increases to $99. It currently comes in silver, polished gold, and matte black and works with iOS and Android devices. Customers can select from eight ring sizes and three colors.
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