When it was founded in 2015, artificial intelligence research lab OpenAI was a nonprofit organization. The idealistic mission: to make sure the high-stakes work they were doing on artificial intelligence served the whole world. This was necessary because — according to the founders’ fervent belief, at least — it would transform the whole world.
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OpenAI is transitioning to a for-profit business. The stakes are enormous.
In some ways since then, OpenAI has succeeded beyond its wildest dreams. “General artificial intelligence” sounded like a pipe dream in 2015, but today we have talking, interactive, creative AI that can pass most tests of human competence we’ve put it to. Many serious people believe that full general intelligence is just around the corner. OpenAI, which in the years since its founding morphed from a nonprofit lab into one of the most highly valued startups in history, has been at the center of that transformation. (Disclosure: Vox Media is one of several publishers that has signed partnership agreements with OpenAI. Our reporting remains editorially independent.)
In other ways, of course, things have been a bit of a mess. Even as it basically became a business, OpenAI used nonprofit governance to keep the company focused on its mission. OpenAI CEO Sam Altman reassured Congress he had no equity in the company, and the nonprofit board still held all authority to change course if they thought the company had gone astray from its mission.
But that ultimately put the board at odds with Altman last November in a messy conflict that the CEO ultimately won. Nearly the entire original leadership team departed. In the year since, the board has largely been replaced and high-profile employees have left the company in waves, some of them warning they no longer believe OpenAI will build superintelligence responsibly. Microsoft, OpenAI’s largest investor, increasingly seems eager for the company to stop building superintelligence and start building a profitable product.
Now, OpenAI is attempting a transition to a more conventional corporate structure, reportedly one where it will be a for-profit public benefit corporation like its rival Anthropic. But nonprofit to for-profit conversions are rare, and misinformation has swirled about what, exactly, “OpenAI becoming a for-profit company” even means.
Elon Musk, who co-founded OpenAI but left after a leadership dispute, paints the for-profit transition as a naked power grab, arguing in a recent lawsuit that Altman and his associates “systematically drained the non-profit of its valuable technology and personnel” in a scheme to get rich off a company that had been founded as a charity. (OpenAI has moved to dismiss Musk’s lawsuit, arguing that it is an “increasingly blusterous campaign to harass OpenAI for his own competitive advantage”).
While Musk — who has his own reasons to be competitive with OpenAI — is among the more vocal critics, many people seem to be under the impression that the company could just slap on a new “for-profit” label and call it a day.
Can you really do that? Start a charity, with all the advantages of nonprofit status, and then declare one day it’s a for-profit company? No, you can’t, and it’s important to understand that OpenAI isn’t doing that.
Rather, nonprofit lawyers told me that what’s almost certainly going on is a complicated and fraught negotiation: the sale of all of the OpenAI nonprofit’s valuable assets to the new for-profit entity, in exchange for the nonprofit continuing to exist and becoming a major investor in the new for-profit entity.
The key question is how much are those assets worth, and can the battered and bruised nonprofit board get a fair deal out of OpenAI (and Microsoft)?
So far, this high-stakes wrangling has taken place almost entirely behind the scenes, and many of the crucial questions have gotten barely any public coverage at all. “I’ve been really kind of baffled at the lack of curiosity about where the value goes that this nonprofit has,” nonprofit law expert Timothy Ogden told me.
Nonprofit law might seem abstruse, which is why most coverage of OpenAI’s transition hasn’t dug into any of the messy details. But those messy details involve tens of billions of dollars, all of which appear to be up for negotiation. The results will dramatically affect how much sway Microsoft has with OpenAI going forward and how much of the company’s value is still tied to its founding mission.
This might seem like something that only matters for OpenAI shareholders, but the company is one of the few that may just have a chance of creating world-changing artificial intelligence. If the public wants a transparent and open process from OpenAI, they have to understand what the law actually allows and who is responsible for following it so we can be sure that OpenAI pursues this transition in a transparent and accountable way.
How OpenAI went from nonprofit to megacorp
In 2015, OpenAI was a nonprofit research organization. It told the IRS in a filing for nonprofit status that its mission was to “advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return.”
Understanding OpenAI’s expansive reach
OpenAI, the maker of ChatGPT, is one of the most important companies in artificial intelligence and one of the most controversial. I’ve been covering the ins and outs of OpenAI for years; here are some highlights:
Have questions or comments? Email me at kelsey.piper@vox.com.
By 2019, that idealistic nonprofit model was running into some trouble. OpenAI had attracted an incredible staff and published some very impressive research. But it was becoming clear that the lofty goal the company had set itself — building general artificial intelligence, machines that can do everything humans can do — was going to be very expensive. It was naturally hard to raise billions of dollars for an effort that was meant to be nonprofit. “We realized that we’d reached the limits of our fundraising ability as a pure nonprofit,” co-founder Ilya Sutskever (who has since departed the company) told me at the time.
The company would attempt to split the difference with a hybrid structure: a nonprofit board controlling a for-profit company. An additional twist: Investors in the for-profit company’s returns were capped at 100x their original investments so that, if world-altering superintelligence was achieved as the OpenAI leadership believed it might, the benefits would accrue to all humanity and not just investors. After all, investors needed to be enticed to invest, but if the company truly ended material scarcity and built a God on Earth, as they essentially said they wanted to, the hope was that more than just the investors would come out ahead.
The nonprofit, therefore, was still supposed to be preeminent. “It would be wise to view any investment in OpenAI Global, LLC in the spirit of a donation,” an enormous black-and-pink disclaimer box on OpenAI’s website alerts would-be investors, “with the understanding that it may be difficult to know what role money will play in a post-AGI world. The Company exists to advance OpenAl, Inc.‘s mission of ensuring that safe artificial general intelligence is developed and benefits all of humanity. The Company’s duty to this mission and the principles advanced in the OpenAl, Inc. Charter take precedence over any obligation to generate a profit.”
One might expect that a prominent disclaimer like that would give commercial investors pause. You would be mistaken. OpenAI had Altman, a fantastic fundraiser, at the helm; its flagship product, ChatGPT, was the fastest app to 100 million users. The company was a gamble, but it was the kind of gamble investors can’t wait to get in on.
But that was then, and this is now. In 2023, in an unexpected and disastrously under-explained move, the nonprofit board fired OpenAI CEO Sam Altman. The board had that authority, of course — it was preeminent — but the execution was shockingly clumsy. The timing of the firing looked likely to disrupt an opportunity for employees to sell millions of dollars of stock in the company. The board gave a few examples of underhanded, bizarre, and dishonest behavior by Altman, including being “not consistently candid” with the board. (One board member later expanded the allegations, saying that Altman had lied to board members about private conversations with other board members, but provided nothing as clear as confused and frustrated employees hoped.)
Employees threatened to resign en masse. Microsoft offered to hire them all and reconstitute the company. Sutskever, who was among the board members who’d voted for Altman’s removal, suddenly changed his mind and voted for Altman to stay. That meant the members who had fired Altman were suddenly in the minority. Two of the board members who had opposed Altman resigned, and the once and future CEO returned to the helm.
Many people concluded that it had been a serious mistake to try to run a company worth 11 figures as a nonprofit instead of as the decidedly for-profit company it was clearly operating as, whatever its bylaws might say. So it’s not surprising that ever since the aborted Altman coup, rumors swirled that OpenAI meant to transition to a fully for-profit entity.
In the last few weeks, those rumors have gotten much more concrete. OpenAI’s latest funding round has been reported to include commitments that the nonprofit-to-for-profit transition will get done in the next two years on pain of the more than $6 billion raised being paid back to those investors. Microsoft and OpenAI — both of whom have enormous amounts to gain in the wrangling over who owns the resulting for-profit company — have hired dueling investment banks to negotiate the details.
We are moving into a new era for OpenAI, and it remains to be seen what that will mean for the humble nonprofit that has ended up owning tens of billions of dollars of the company’s assets.
How do you turn a charity into a for-profit?
If OpenAI were really just taking the nonprofit organization’s assets and declaring them “converted” into a for-profit — as if they were playing a game of tag and suddenly decided a tree was “base” — that would absolutely be illegal. The takeaway, though, shouldn’t be that a crime is happening in plain sight, but that something much more complicated is being negotiated. Nonprofit law experts I talked to said that the situation was being widely and comprehensively misunderstood.
Here are the rules. First off, assets accumulated by a nonprofit cannot be used for private benefit. “It’s the job of the board first, and then the regulators and the court, to ensure that the promise that was made to the public to pursue the charitable interest is kept,” UCLA law professor Jill Horwitz told Reuters.
If it looks as though a nonprofit isn’t pursuing its charitable interest, and especially if it appears to be handing some of its board members bargain-bin deals on billion-dollar assets during a transition to for-profit status? That will have the IRS investigating, along with the state’s Attorney General.
But a nonprofit can sell anything it owns. If a nonprofit owns a piece of land, for example, and it wants to sell that land so that it has more money to spend on its mission, it’s all good. If the nonprofit sold the land for well below market value to the director’s nephew, it would be a clear crime, and the IRS or the state’s Attorney General might well investigate. The nonprofit has to sell the land at a fair market price, take the money, and keep using the money for its nonprofit work.
At a much larger scale, that is exactly what is at stake in the OpenAI transition. The nonprofit owns some assets: control over the for-profit company, a lot of AI IP from OpenAI’s proprietary research, and all future returns from the for-profit company once they exceed the 100x cap set up by the capped profit company — which, should the company achieve its goals, could well be limitless. If the new OpenAI wants to extract all of its assets from the nonprofit, it has to pay the full market price. And the nonprofit has to continue to exist and to use the money it has earned in that transfer for its mission of ensuring that AI benefits all of humanity.
There have been a few other cases in corporate legal history of a nonprofit making the transition to a for-profit company, most prominently the credit card company Mastercard, which was founded as a nonprofit collaboration among banks. When that situation happens, the nonprofit’s assets still belong to the nonprofit.
Mastercard, in the course of transitioning to a public company, ended up founding the now-$47 billion Mastercard Foundation, one of the world’s wealthiest private foundations. Far from the for-profit walking away with all the nonprofit’s assets, the for-profit emerges as an independent company and the nonprofit emerges not only still extant but very rich.
OpenAI’s board has indicated that this is exactly what they are doing. “Any potential restructuring would ensure the nonprofit continues to exist and thrive, and receives full value for its current stake in the OpenAI for-profit with an enhanced ability to pursue its mission.” OpenAI board chairman Bret Taylor, a technologist and CEO, told me in a statement. (What counts as “full value”? We’ll come back to that.)
Outside actors, too, expect to be applying oversight to make sure that the nonprofit gets a fair deal. A spokesperson for the California Attorney General’s office told the Information that their office is “committed to protecting charitable assets for their intended purpose.” OpenAI is registered in Delaware, but the company operates primarily in California, and California’s AG is much less deferential to business than Delaware’s.
So, the OpenAI entity will definitely owe the nonprofit mind-boggling amounts of money. Depending who you ask, it could be between $37 billion and $80 billion. The OpenAI for-profit entity does not have that kind of money on hand — don’t forget that OpenAI is projected to lose tens of billions of dollars in the years ahead — so the plans in the works are reportedly for the for-profit to make the nonprofit a major shareholder in the for-profit.
The Information reported last week that “the nonprofit is expected to own at least a 25% stake in the for-profit — which on paper would be worth at least $37 billion.” In other words, rather than buying the assets from the non-profit with cash, OpenAI will trade equity.
That’s a lot of money. But many experts I spoke to thought it was actually much too low.
What’s a fair price for control of a mega company?
Everyone agrees that the OpenAI board is required to negotiate and receive a fair price for everything the OpenAI nonprofit owns that the for-profit is purchasing. But what counts as a fair price? That’s an open question, one that people stand to earn or lose tens of billions of dollars by getting answered in their favor.
But first: What does the OpenAI nonprofit own?
It owns a lot of OpenAI’s IP. How much exactly is highly confidential, but some experts speculate that the $37 billion number is probably a reflection of the easily measured, straightforward assets of the nonprofit, like its IP and business agreements.
Secondly, and most crucially, it owns full control over the OpenAI for-profit. As part of this deal, it is definitely going to give that up, either becoming a minority shareholder or ending up with nonvoting shares entirely. That is, substantially, the whole point of the nonprofit-to-for-profit conversion: After Altman’s ouster, the Wall Street Journal reported, “[I]nvestors began pushing OpenAI to turn into a more typical company.” Investors throwing around billions of dollars don’t want a nonprofit board to be able to fire the CEO because they’re worried he’s too dishonest to make good decisions around powerful new technology. Investors want a normal board that will fire the CEO for normal reasons, like that he’s not maximizing shareholder value.
Control is generally worth a lot more, in for-profit companies, than shares that come without control — often something like 40 percent more. So if the nonprofit is getting a fair deal, it should get some substantive compensation in exchange for giving up control of the company.
Thirdly, investors in OpenAI under its old business model agreed to a “capped profit” model. For most investors, that cap was set at 100x their original investment, so if they invested $1 million, they would get a maximum of $100 million in return. Above that cap, all returns would go to the nonprofit. The logic for this setup was that, under most circumstances, it’s the same as investing in a normal company. Investments don’t usually produce 100x returns, after all, with the exception of early investments in massively successful tech companies like Google or Amazon.
The capped profit setup would be most significant in the unlikely world where OpenAI attained its ambitious goals and built an AI that fundamentally transformed the world economy. (How likely is that? Experts disagree, rather heatedly, but we shouldn’t discount it altogether.) If that does happen, its value will be nearly unfathomably huge. “OpenAI’s value is mostly in the extreme upside,” AI analyst Zvi Mowshowitz wrote in an analysis of the valuation question.
The company might fail entirely; it might muddle along as a midsized company. But it also might be worth trillions of dollars, or more than that, and most investors are investing on the premise it might be worth trillions of dollars. That means the share of profits owned by the nonprofit would also be worth trillions of dollars. “Most future profits still likely flow to the nonprofit,” Mowshowitz concludes. “OpenAI is shooting for the stars. As every VC in this spot knows, it is the extreme upside that matters. That is what the nonprofit is selling. They shouldn’t sell it cheap.”
So what would be an appropriate valuation? $60 billion? $100 billion? Mowshowitz’s analysis is that a fair price would involve the nonprofit still owning a majority of shares in the for-profit, which is to say at least $80 billion. (Presumably these would be nonvoting shares.)
The only people with full information are the ones with access to the company’s confidential balance sheets, and they aren’t talking. OpenAI and Microsoft will be negotiating the answer to the question, but it’s not clear that either of them particularly wants the nonprofit to get a valuation that reflects, for example, the expected value of the profits in excess of the cap because there’s more money for everyone else who wants a piece of the pie if the nonprofit gets less.
There are two forces working toward the nonprofit getting fair compensation: the nonprofit board — whose members are capable people, but also people handpicked by Altman not to get ideas and get in the way of his control of the company — and the law. Experts I spoke with were a bit cynical about the board’s willingness to hold out for a good deal in what is an extremely awkward circumstance for it. “We have kind of already seen what’s going on with the OpenAI board,” Ogden told me.
“I think the common understanding is they’re friendly to Sam Altman, and the ones who were trying to slow things down or protect the nonprofit purpose have left,” Rose Chan Loui, the director of UCLA Law’s nonprofit program, observed to the Transformer.
If the board is inclined to go with the flow, the Delaware Attorney General or the IRS could object. These are fundamentally complicated questions about the valuation of a private company, and the law isn’t always good at consistent and principled enforcement in cases like this one. “When you’re talking about numbers like $150 billion,” UCLA law professor Jill Horwitz warned, “the law has a way of getting weak.”
Does that mean that Elon Musk’s allegation — that we’re witnessing a bait-and-switch before our eyes, a massive theft of resources that were originally dedicated to the common good — is right after all? I’m not inclined to grant him that much.
Firstly, having spoken to OpenAI leadership and OpenAI employees over the six years I’ve been reporting on the company, I genuinely come away with the impression that the bait-and-switch, to the extent it happened, was completely unintentional.
In 2015, the involved parties really were — including in private emails leaked in Musk’s lawsuits — convinced that a research organization serving the public was the way to achieve their mission. And then over the next few years, as the power of big machine learning models became apparent, they became sincerely convinced they needed to find clever ways to raise money for their research. In 2019, when I spoke with Brockman and Sutskever, they were enthusiastic about their capped profit structure and saw it as a model for how a company could raise money but ensure most of its benefits if it succeeded went to humanity as a whole.
Altman has a habit of being all things to all people, even when that may require being less than truthful. His detractors say he’s “deceptive, manipulative, and worse”, and even his supporters will say he’s “extremely good at becoming powerful,” which VCs might consider more of a compliment than the general public does.
But I don’t think Altman was aiming for this predicament. OpenAI did not inflict its current legal headache on itself out of cunning chicanery, but out of a desire to satisfy a number of different early stakeholders, many of them true believers. It was due chiefly to understandable failures of foresight about how much power corporate governance law would really have once employees had millions riding on the company’s continued fundraising and once investors had billions riding on its ability to make a profit.
Secondly, I think it’s far too soon to call this a bait-and-switch. The nonprofit’s control of OpenAI was meant to give it the power to stop the company from putting profits before the mission. But it turns out that being on a nonprofit board does not come with enough access to the company, or enough real power, to productively turn OpenAI away from the brink, as we discovered last November.
It seems entirely possible that a massive and highly capitalized nonprofit foundation with the aim of ensuring AI benefits humanity is a better approach than a corporate governance agreement with power on paper and none in practice. If the nonprofit gets massively undervalued in the conversion and shooed away with a quarter of the company when more careful estimates suggest it currently controls a majority of the company’s value, then we can call it a bait-and-switch.
But that hasn’t happened. The correct attitude is to wait and see, to demand transparency, to hold the board to account for getting the valuation it is legally obligated to pursue, and to pursue OpenAI to the full extent of the law if it ends up convincing the board to give up its extraordinary bequest at bargain-basement prices.
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Apocalipsis Biosciencias para desarrollar Géminis para la infección en pacientes con quemaduras graves
– Esta nueva indicación es otro paso para desbloquear todo el potencial de la plataforma Gemini –
San Diego-(Business Wire)-$ Revb #GÉMINIS–Apocalipsis Biosciences, Inc. (NASDAQ: RevB) (la “empresa” o “revelación”), una compañía de ciencias de la vida de etapas clínicas que se centra en reequilibrar la inflamación para optimizar la salud, anunció una nueva indicación de objetivo para Géminis para la prevención de la infección en pacientes con quemaduras graves que requieren hospitalización (el Gema-PBI programa). El uso de Géminis para la prevención de la infección en pacientes con quemaduras severas, así como la prevención de la infección después de la cirugía (el Gema-PSI programa) son parte de la revelación familiar de patentes anteriormente con licencia de la Universidad de Vanderbilt.
“Estamos muy contentos de colaborar con el equipo de Apocalipsis para el avance de Géminis para la prevención de la infección en esta población de pacientes desatendida”, dijo Dra. Julia BohannonProfesor Asociado, Departamento de Anestesiología, Departamento de Patología, Microbiología e Inmunología, Universidad de Vanderbilt. “Creemos que la actividad de biomarcador clínico observada con Gemini se correlaciona fuertemente con nuestra experiencia preclínica en modelos de quemaduras de infecciones”.
El equipo de investigación de Vanderbilt demostrado El tratamiento posterior a la quemadura reduce significativamente la gravedad y la duración de la infección pulmonar de Pseudomonas, así como un nivel general reducido de inflamación en un modelo preclínico.
“La prevención de la infección en pacientes severamente quemados es un esfuerzo importante y complementa que la revelación laboral ha completado hasta la fecha”, dijo “, dijo”, dijo James RolkeCEO de Revelation “El programa Gemini-PBI puede ofrecer varias oportunidades regulatorias, de desarrollo y financiación que la compañía planea explorar”.
Sobre quemaduras e infección después de quemar
Las quemaduras son lesiones en la piel que involucran las dos capas principales: la epidermis externa delgada y/o la dermis más gruesa y profunda. Las quemaduras pueden ser el resultado de una variedad de causas que incluyen fuego, líquidos calientes, productos químicos (como ácidos fuertes o bases fuertes), electricidad, vapor, radiación de radiografías o radioterapia, luz solar o luz ultravioleta. Cada año, aproximadamente medio millón de estadounidenses sufren lesiones por quemaduras que requieren intervención médica. Si bien la mayoría de las lesiones por quemaduras no requieren ingreso a un hospital, se admiten alrededor de 40,000 pacientes, y aproximadamente 30,000 de ellos necesitan tratamiento especializado en un centro de quemaduras certificadas.
El número total anual de muertes relacionadas con quemaduras es de aproximadamente 3.400, siendo la infección invasiva la razón principal de la muerte después de las primeras 24 horas. La tasa de mortalidad general para pacientes con quemaduras graves es de aproximadamente 3.3%, pero esto aumenta al 20.6% en pacientes con quemaduras con lesión cutánea de quemaduras y inhalación, versus 10.5% por lesión por inhalación solo. La infección invasiva, incluida la sepsis, es la causa principal de la muerte después de la lesión por quemaduras, lo que representa aproximadamente el 51% de las muertes.
Actualmente no hay tratamientos aprobados para prevenir la infección sistémica en pacientes con quemaduras.
Sobre Géminis
Géminis es una formulación propietaria y propietaria de disacárido hexaacil fosforilada (PHAD (PHAD®) que reduce el daño asociado con la inflamación al reprogramarse del sistema inmune innato para responder al estrés (trauma, infección, etc.) de manera atenuada. La revelación ha realizado múltiples estudios preclínicos que demuestran el potencial terapéutico de Géminis en las indicaciones objetivo. Revelación anunciado previamente Datos clínicos positivos de fase 1 para el tratamiento intravenoso con Géminis. El punto final de seguridad primario se cumplió en el estudio de fase 1, y los resultados demostraron la actividad farmacodinámica estadísticamente significativa como se observó a través de los cambios esperados en múltiples biomarcadores, incluida la regulación positiva de IL-10.
Géminis se está desarrollando para múltiples indicaciones, incluso como pretratamiento para prevenir o reducir la gravedad y la duración de la lesión renal aguda (programa Gemini-AKI), y como pretratamiento para prevenir o reducir la gravedad y la duración de la infección posquirúrgica (programa GEMINI-PSI). Además, Gemini puede ser un tratamiento para detener o retrasar la progresión de la enfermedad renal crónica (programa Gemini-CKD).
Acerca de Apocalipsis Biosciences, Inc.
Revelation Biosciences, Inc. es una compañía de ciencias de la vida en estadio clínico centrada en aprovechar el poder de la inmunidad entrenada para la prevención y el tratamiento de la enfermedad utilizando su formulación patentada Géminis. Revelation tiene múltiples programas en curso para evaluar Géminis, incluso como prevención de la infección posquirúrgica, como prevención de lesiones renales agudas y para el tratamiento de la enfermedad renal crónica.
Para obtener más información sobre Apocalipsis, visite www.revbiosciences.com.
Declaraciones con avance
Este comunicado de prensa contiene declaraciones prospectivas definidas en la Ley de Reforma de Litigios de Valores Privados de 1995, según enmendada. Las declaraciones prospectivas son declaraciones que no son hechos históricos. Estas declaraciones prospectivas generalmente se identifican por las palabras “anticipar”, “creer”, “esperar”, “estimar”, “plan”, “perspectiva” y “proyecto” y otras expresiones similares. Advirtemos a los inversores que las declaraciones prospectivas se basan en las expectativas de la gerencia y son solo predicciones o declaraciones de las expectativas actuales e involucran riesgos, incertidumbres y otros factores conocidos y desconocidos que pueden hacer que los resultados reales sean materialmente diferentes de los previstos por las declaraciones de prospección. Apocalipsis advierte a los lectores que no depositen una dependencia indebida de tales declaraciones de vista hacia adelante, que solo hablan a partir de la fecha en que se hicieron. Los siguientes factores, entre otros, podrían hacer que los resultados reales difieran materialmente de los descritos en estas declaraciones prospectivas: la capacidad de la revelación para cumplir con sus objetivos financieros y estratégicos, debido a, entre otras cosas, la competencia; la capacidad de la revelación para crecer y gestionar la rentabilidad del crecimiento y retener a sus empleados clave; la posibilidad de que la revelación pueda verse afectada negativamente por otros factores económicos, comerciales y/o competitivos; riesgos relacionados con el desarrollo exitoso de los candidatos de productos de Apocalipsis; la capacidad de completar con éxito los estudios clínicos planificados de sus candidatos de productos; El riesgo de que no podamos inscribir completamente nuestros estudios clínicos o la inscripción llevará más tiempo de lo esperado; riesgos relacionados con la aparición de eventos de seguridad adversos y/o preocupaciones inesperadas que pueden surgir de los datos o análisis de nuestros estudios clínicos; cambios en las leyes o regulaciones aplicables; Iniciación esperada de los estudios clínicos, el momento de los datos clínicos; El resultado de los datos clínicos, incluido si los resultados de dicho estudio son positivos o si se puede replicar; El resultado de los datos recopilados, incluido si los resultados de dichos datos y/o correlación se pueden replicar; el momento, los costos, la conducta y el resultado de nuestros otros estudios clínicos; El tratamiento anticipado de datos clínicos futuros por parte de la FDA, la EMA u otras autoridades reguladoras, incluidos si dichos datos serán suficientes para su aprobación; el éxito de futuras actividades de desarrollo para sus candidatos de productos; posibles indicaciones para las cuales se pueden desarrollar candidatos de productos; la capacidad de revelación para mantener la lista de sus valores en NASDAQ; la duración esperada sobre la cual los saldos de Apocalipsis financiarán sus operaciones; y otros riesgos e incertidumbres descritos en este documento, así como aquellos riesgos e incertidumbres discutidos de vez en cuando en otros informes y otras presentaciones públicas con la SEC por Apocalipsis.
Contactos
Mike Porter
Relaciones con inversores
Porter Levay & Rose Inc.
Correo electrónico: mike@plrinvest.com
Chester Zygmont, III
Director financiero
Apocalipsis Biosciences Inc.
Correo electrónico: czygmont@revbiosciences.com
An illustration photograph taken on Feb. 20, 2025 shows Grok, DeepSeek and ChatGPT apps displayed on a phone screen. The Justice Department’s 2020 complaint against Google has few mentions of artificial intelligence or AI chatbots. But nearly five years later, as the remedy phase of the trial enters its second week of testimony, the focus has shifted to AI.
Michael M. Santiago/Getty Images/Getty Images North America
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Michael M. Santiago/Getty Images/Getty Images North America
When the U.S. Department of Justice originally brought — and then won — its case against Google, arguing that the tech behemoth monopolized the search engine market, the focus was on, well … search.
Back then, in 2020, the government’s antitrust complaint against Google had few mentions of artificial intelligence or AI chatbots. But nearly five years later, as the remedy phase of the trial enters its second week of testimony, the focus has shifted to AI, underscoring just how quickly this emerging technology has expanded.
In the past few days, before a federal judge who will assess penalties against Google, the DOJ has argued that the company could use its artificial intelligence products to strengthen its monopoly in online search — and to use the data from its powerful search index to become the dominant player in AI.
In his opening statements last Monday, David Dahlquist, the acting deputy director of the DOJ’s antitrust civil litigation division, argued that the court should consider remedies that could nip a potential Google AI monopoly in the bud. “This court’s remedy should be forward-looking and not ignore what is on the horizon,” he said.
Dahlquist argued that Google has created a system in which its control of search helps improve its AI products, sending more users back to Google search — creating a cycle that maintains the tech company’s dominance and blocks competitors out of both marketplaces.
The integration of search and Gemini, the company’s AI chatbot — which the DOJ sees as powerful fuel for this cycle — is a big focus of the government’s proposed remedies. The DOJ is arguing that to be most effective, those remedies must address all ways users access Google search, so any penalties approved by the court that don’t include Gemini (or other Google AI products now or in the future) would undermine their broader efforts.
Department of Justice lawyer David Dahlquist leaves the Washington, D.C. federal courthouse on Sept. 20, 2023 during the original trial phase of the antitrust case against Google.
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Jose Luis Magana/AP/FR159526 AP
AI and search are connected like this: Search engine indices are essentially giant databases of pages and information on the web. Google has its own such index, which contains hundreds of billions of webpages and is over 100,000,000 gigabytes, according to court documents. This is the data Google’s search engine scans when responding to a user’s query.
AI developers use these kinds of databases to build and train the models used to power chatbots. In court, attorneys for the DOJ have argued that Google’s Gemini pulls information from the company’s search index, including citing search links and results, extending what they say is a self-serving cycle. They argue that Google’s ability to monopolize the search market gives it user data, at a huge scale — an advantage over other AI developers.
The Justice Department argues Google’s monopoly over search could have a direct effect on the development of generative AI, a type of artificial intelligence that uses existing data to create new content like text, videos or photos, based on a user’s prompts or questions. Last week, the government called executives from several major AI companies, like OpenAI and Perplexity, in an attempt to argue that Google’s stranglehold on search is preventing some of those companies from truly growing.
The government argues that to level the playing field, Google should be forced to open its search data — like users’ search queries, clicks and results — and license it to other competitors at a cost.
This is on top of demands related to Google’s search engine business, most notably that it should be forced to sell off its Chrome browser.
Google flatly rejects the argument that it could monopolize the field of generative AI, saying competition in the AI race is healthy. In a recent blog post on Google’s website, Lee-Anne Mulholland, the company’s vice president of regulatory affairs, wrote that since the federal judge first ruled against Google over a year ago, “AI has already rapidly reshaped the industry, with new entrants and new ways of finding information, making it even more competitive.”
In court, Google’s lawyers have argued that there are a host of AI companies with chatbots — some of which are outperforming Gemini. OpenAI has ChatGPT, Meta has MetaAI and Perplexity has Perplexity AI.
“There is no shortage of competition in that market, and ChatGPT and Meta are way ahead of everybody in terms of the distribution and usage at this point,” said John E. Schmidtlein, a lawyer for Google, during his opening statement. “But don’t take my word for it. Look at the data. Hundreds and hundreds of millions of downloads by ChatGPT.”
Competing in a growing AI field
It should be no surprise that AI is coming up so much at this point in the trial, said Alissa Cooper, the executive director of the Knight-Georgetown Institute, a nonpartisan tech research and policy center at Georgetown University focusing on AI, disinformation and data privacy.
“If you look at search as a product today, you can’t really think about search without thinking about AI,” she said. “I think the case is a really great opportunity to try to … analyze how Google has benefited specifically from the monopoly that it has in search, and ensure that the behavior that led to that can’t be used to gain an unfair advantage in these other markets which are more nascent.”
Having access to Google’s data, she said, “would provide them with the ability to build better chatbots, build better search engines, and potentially build other products that we haven’t even thought of.”
To make that point, the DOJ called Nick Turley, OpenAI’s head of product for ChatGPT, to the stand last Tuesday. During a long day of testimony, Turley detailed how without access to Google’s search index and data, engineers for the growing company tried to build their own.
ChatGPT, a large language model that can generate human-like responses, engage in conversations and perform tasks like explaining a tough-to-understand math lesson, was never intended to be a product for OpenAI, Turley said. But once it launched and went viral, the company found that people were using it for a host of needs.
Though popular, ChatGPT had its drawbacks, like the bot’s limited “knowledge,” Turley said. Early on, ChatGPT was not connected to the internet and could only use information that it had been fed up to a certain point in its training. For example, Turley said, if a user asked “Who is the president?” the program would give a 2022 answer — from when its “knowledge” effectively stopped.
OpenAI couldn’t build their own index fast enough to address their problems; they found that process incredibly expensive, time consuming and potentially years from coming to fruition, Turley said.
So instead, they sought a partnership with a third party search provider. At one point, OpenAI tried to make a deal with Google to gain access to their search, but Google declined, seeing OpenAI as a direct competitor, Turley testified.
But Google says companies like OpenAI are doing just fine without gaining access to the tech giant’s own technology — which it spent decades developing. These companies just want “handouts,” said Schmidtlein.
On the third day of the remedy trial, internal Google documents shared in court by the company’s lawyers compared how many people are using Gemini versus its competitors. According to those documents, ChatGPT and MetaAI are the two leaders, with Gemini coming in third.
They showed that this March, Gemini saw 35 million active daily users and 350 million monthly active users worldwide. That was up from 9 million daily active users in October 2024. But according to those documents, Gemini was still lagging behind ChatGPT, which reached 160 million daily users and around 600 million active users in March.
These numbers show that competitors have no need to use Google’s search data, valuable intellectual property that the tech giant spent decades building and maintaining, the company argues.
“The notion that somehow ChatGPT can’t get distribution is absurd,” Schmidtlein said in court last week. “They have more distribution than anyone.”
Google’s exclusive deals
In his ruling last year, U.S. District Judge Amit Mehta said Google’s exclusive agreements with device makers, like Apple and Samsung, to make its search engine the default on those companies’ phones helped maintain its monopoly. It remains a core issue for this remedy trial.
Now, the DOJ is arguing that Google’s deals with device manufacturers are also directly affecting AI companies and AI tech.
In court, the DOJ argued that Google has replicated this kind of distribution deal by agreeing to pay Samsung what Dahlquist called a monthly “enormous sum” for Gemini to be installed on smartphones and other devices.
Last Wednesday, the DOJ also called Dmitry Shevelenko, Perplexity’s chief business officer, to testify that Google has effectively cut his company out from making deals with manufacturers and mobile carriers.
Perplexity AIs not preloaded on any mobile devices in the U.S., despite many efforts to get phone companies to establish Perplexity as a default or exclusive app on devices, Shevelenko said. He compared Google’s control in that space to that of a “mob boss.”
But Google’s attorney, Christopher Yeager, noted in questioning Shevelenko that Perplexity has reached a valuation of over $9 billion — insinuating the company is doing just fine in the marketplace.
Despite testifying in court (for which he was subpoenaed, Shevelenko noted), he and other leaders at Perplexity are against the breakup of Google. In a statement on the company’s website, the Perplexity team wrote that neither forcing Google to sell off Chrome nor to license search data to its competitors are the best solutions. “Neither of these address the root issue: consumers deserve choice,” they wrote.
Google and Alphabet CEO Sundar Pichai departs federal court after testifying in October 2023 in Washington, DC. Pichai testified to defend his company in the original antitrust trial. Pichai is expected to testify again during the remedy phase of the legal proceedings.
Drew Angerer/Getty Images/Getty Images North America
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Drew Angerer/Getty Images/Getty Images North America
What to expect next
This week the trial continues, with the DOJ calling its final witnesses this morning to testify about the feasibility of a Chrome divestiture and how the government’s proposed remedies would help rivals compete. On Tuesday afternoon, Google will begin presenting its case, which is expected to feature the testimony of CEO Sundar Pichai, although the date of his appearance has not been specified.
Closing arguments are expected at the end of May, and then Mehta will make his ruling. Google says once this phase is settled the company will appeal Mehta’s ruling in the underlying case.
Whatever Mehta decides in this remedy phase, Cooper thinks it will have effects beyond just the business of search engines. No matter what it is, she said, “it will be having some kind of impact on AI.”
Google is a financial supporter of NPR.
Noticias
API de Meta Oleleshes Llama que se ejecuta 18 veces más rápido que OpenAI: Cerebras Partnership ofrece 2.600 tokens por segundo
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Meta anunció hoy una asociación con Cerebras Systems para alimentar su nueva API de LLAMA, ofreciendo a los desarrolladores acceso a velocidades de inferencia hasta 18 veces más rápido que las soluciones tradicionales basadas en GPU.
El anuncio, realizado en la Conferencia inaugural de desarrolladores de Llamacon de Meta en Menlo Park, posiciona a la compañía para competir directamente con Operai, Anthrope y Google en el mercado de servicios de inferencia de IA en rápido crecimiento, donde los desarrolladores compran tokens por miles de millones para impulsar sus aplicaciones.
“Meta ha seleccionado a Cerebras para colaborar para ofrecer la inferencia ultra rápida que necesitan para servir a los desarrolladores a través de su nueva API de LLAMA”, dijo Julie Shin Choi, directora de marketing de Cerebras, durante una sesión de prensa. “En Cerebras estamos muy, muy emocionados de anunciar nuestra primera asociación HyperScaler CSP para ofrecer una inferencia ultra rápida a todos los desarrolladores”.
La asociación marca la entrada formal de Meta en el negocio de la venta de AI Computation, transformando sus populares modelos de llama de código abierto en un servicio comercial. Si bien los modelos de LLAMA de Meta se han acumulado en mil millones de descargas, hasta ahora la compañía no había ofrecido una infraestructura en la nube de primera parte para que los desarrolladores creen aplicaciones con ellos.
“Esto es muy emocionante, incluso sin hablar sobre cerebras específicamente”, dijo James Wang, un ejecutivo senior de Cerebras. “Openai, Anthrope, Google: han construido un nuevo negocio de IA completamente nuevo desde cero, que es el negocio de inferencia de IA. Los desarrolladores que están construyendo aplicaciones de IA comprarán tokens por millones, a veces por miles de millones. Y estas son como las nuevas instrucciones de cómputo que las personas necesitan para construir aplicaciones AI”.
Breaking the Speed Barrier: Cómo modelos de Llama de Cerebras Supercharges
Lo que distingue a la oferta de Meta es el aumento de la velocidad dramática proporcionado por los chips de IA especializados de Cerebras. El sistema de cerebras ofrece más de 2.600 fichas por segundo para Llama 4 Scout, en comparación con aproximadamente 130 tokens por segundo para ChatGPT y alrededor de 25 tokens por segundo para Deepseek, según puntos de referencia del análisis artificial.
“Si solo se compara con API a API, Gemini y GPT, todos son grandes modelos, pero todos se ejecutan a velocidades de GPU, que son aproximadamente 100 tokens por segundo”, explicó Wang. “Y 100 tokens por segundo están bien para el chat, pero es muy lento para el razonamiento. Es muy lento para los agentes. Y la gente está luchando con eso hoy”.
Esta ventaja de velocidad permite categorías completamente nuevas de aplicaciones que antes no eran prácticas, incluidos los agentes en tiempo real, los sistemas de voz de baja latencia conversacional, la generación de código interactivo y el razonamiento instantáneo de múltiples pasos, todos los cuales requieren encadenamiento de múltiples llamadas de modelo de lenguaje grandes que ahora se pueden completar en segundos en lugar de minutos.
La API de LLAMA representa un cambio significativo en la estrategia de IA de Meta, en la transición de ser un proveedor de modelos a convertirse en una compañía de infraestructura de IA de servicio completo. Al ofrecer un servicio API, Meta está creando un flujo de ingresos a partir de sus inversiones de IA mientras mantiene su compromiso de abrir modelos.
“Meta ahora está en el negocio de vender tokens, y es excelente para el tipo de ecosistema de IA estadounidense”, señaló Wang durante la conferencia de prensa. “Traen mucho a la mesa”.
La API ofrecerá herramientas para el ajuste y la evaluación, comenzando con el modelo LLAMA 3.3 8B, permitiendo a los desarrolladores generar datos, entrenar y probar la calidad de sus modelos personalizados. Meta enfatiza que no utilizará datos de clientes para capacitar a sus propios modelos, y los modelos construidos con la API de LLAMA se pueden transferir a otros hosts, una clara diferenciación de los enfoques más cerrados de algunos competidores.
Las cerebras alimentarán el nuevo servicio de Meta a través de su red de centros de datos ubicados en toda América del Norte, incluidas las instalaciones en Dallas, Oklahoma, Minnesota, Montreal y California.
“Todos nuestros centros de datos que sirven a la inferencia están en América del Norte en este momento”, explicó Choi. “Serviremos Meta con toda la capacidad de las cerebras. La carga de trabajo se equilibrará en todos estos diferentes centros de datos”.
El arreglo comercial sigue lo que Choi describió como “el proveedor de cómputo clásico para un modelo hiperscalador”, similar a la forma en que NVIDIA proporciona hardware a los principales proveedores de la nube. “Están reservando bloques de nuestro cómputo para que puedan servir a su población de desarrolladores”, dijo.
Más allá de las cerebras, Meta también ha anunciado una asociación con Groq para proporcionar opciones de inferencia rápida, brindando a los desarrolladores múltiples alternativas de alto rendimiento más allá de la inferencia tradicional basada en GPU.
La entrada de Meta en el mercado de API de inferencia con métricas de rendimiento superiores podría potencialmente alterar el orden establecido dominado por Operai, Google y Anthrope. Al combinar la popularidad de sus modelos de código abierto con capacidades de inferencia dramáticamente más rápidas, Meta se está posicionando como un competidor formidable en el espacio comercial de IA.
“Meta está en una posición única con 3 mil millones de usuarios, centros de datos de hiper escala y un gran ecosistema de desarrolladores”, según los materiales de presentación de Cerebras. La integración de la tecnología de cerebras “ayuda a Meta Leapfrog OpenAi y Google en rendimiento en aproximadamente 20X”.
Para las cerebras, esta asociación representa un hito importante y la validación de su enfoque especializado de hardware de IA. “Hemos estado construyendo este motor a escala de obleas durante años, y siempre supimos que la primera tarifa de la tecnología, pero en última instancia tiene que terminar como parte de la nube de hiperescala de otra persona. Ese fue el objetivo final desde una perspectiva de estrategia comercial, y finalmente hemos alcanzado ese hito”, dijo Wang.
La API de LLAMA está actualmente disponible como una vista previa limitada, con Meta planifica un despliegue más amplio en las próximas semanas y meses. Los desarrolladores interesados en acceder a la inferencia Ultra-Fast Llama 4 pueden solicitar el acceso temprano seleccionando cerebras de las opciones del modelo dentro de la API de LLAMA.
“Si te imaginas a un desarrollador que no sabe nada sobre cerebras porque somos una empresa relativamente pequeña, solo pueden hacer clic en dos botones en el SDK estándar de SDK estándar de Meta, generar una tecla API, seleccionar la bandera de cerebras y luego, de repente, sus tokens se procesan en un motor gigante a escala de dafers”, explicó las cejas. “Ese tipo de hacernos estar en el back -end del ecosistema de desarrolladores de Meta todo el ecosistema es tremendo para nosotros”.
La elección de Meta de silicio especializada señala algo profundo: en la siguiente fase de la IA, no es solo lo que saben sus modelos, sino lo rápido que pueden pensarlo. En ese futuro, la velocidad no es solo una característica, es todo el punto.
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