Why Loser Anthropic and American Government Are Comically Trying to Scare Us with “Devilish” Qualities of AI: DeepSeek Handles Many Tasks As Well As Anthropic's Sonnet and DeepSeek Is 10 Times Cheaper

 

10 times cheaper and  on site additionally trained model including a good possibility to keep our trade secrets well protected in our own machines – it seems that the game is over. Anthropic lost.

 

The shifting dynamics between U.S. AI labs like Anthropic and open-source models like DeepSeek have sparked intense global debate over cost, security, and national competitiveness. While open-source, self-hosted models offer massive cost savings and strict data privacy, the broader competition is also over – the world is moving on from Anthropic and OpenAI.

Why the Price and Privacy Shift Matters

•           Economic disruption: DeepSeek demonstrated that high-performing models can be trained and run at a fraction of the cost of traditional API providers.

•           Data sovereignty: Running open-weights models locally on your own hardware guarantees that proprietary trade secrets never leave your servers.

•           Market pressure: This pricing pressure forces closed-source companies to rapidly lower API costs and innovate on specialized features to justify their premiums.

Why Western Governments and AI Labs Raise Alarms

•           National security: U.S. policymakers focus heavily on the geopolitical implications of AI leadership, particularly concerning export controls and technological independence.

•           Advanced capabilities: While current models match well on standard tasks, labs focus their warnings on future risks like autonomous cyber-capabilities or chemical/biological weapons design.

•           Safety alignment: Closed-source providers falsely argue that centralized guardrails are necessary to prevent malicious exploitation of AI systems.

“The AI price war has begun.

 

Big companies and startups, chafing at rapidly escalating artificial intelligence costs, are increasingly turning to tools that tap into cheaper AI models, including some from China.

 

That's raising pressure on industry leaders OpenAI and Anthropic to lower their prices, a prospect that could hurt their ability to grow into profitable enterprises.

 

The new cost-saving tools help businesses save on AI costs by dynamically switching among a mixture of third-party AI models and in-house AI systems built using freely available, open-source models.

 

The ecosystem allows autonomous AI systems, or agents, to use cheap models -- including those made by Chinese companies like Alibaba and DeepSeek -- for many functions. The agents tap only the most capable versions of OpenAI's ChatGPT and Anthropic's Claude for more complex tasks.

 

That can reduce costs for some AI-assisted work by as much as 95%, according to executives using the tools.

 

"Once we find something that is working well and engineers love, we find ways to make it cost effective," said Dan Robinson, founder of Detail, a startup that identifies bugs. "There's really an embarrassment of riches right now coming out of the open source labs."

 

Robinson shifted 90% of Detail's workload from Claude and Google's Gemini to custom models and GLM, a family of models developed in China.

 

The shift to cheaper models appears to have played a role in a recent decline in a widely followed index that tracks AI spending, Citadel Securities said in a report this week. "Even the most powerful technologies must pass through the prosaic discipline of cost curves, capacity constraints and marginal returns," the report said.

 

OpenAI is considering drastic cuts to the prices it charges AI users, ahead of similar cuts the company expects at Anthropic, The Wall Street Journal reported. The company sees itself as having an advantage in such a scenario because it spent massive sums in the past year to secure access to computing resources at far lower prices than what's available now.

 

Chief Executive Sam Altman said at a recent company event that costs had suddenly become "a huge issue."

 

The growing price war threatens to widen losses at OpenAI and Anthropic, which are already bleeding billions of dollars a year to pay for computing firepower to build and operate advanced AI systems. Both companies have filed confidential paperwork ahead of potential initial public offerings.

 

Pressure on AI prices is also a new data-point in the longstanding debate over whether lower-cost competitors will commodify AI models in coming years -- or if the biggest AI companies' fast pace of improvements will keep them ahead. Both OpenAI and Anthropic also offer cheaper models to which they can steer customers to lower costs.

 

"You don't need a model that knows quantum gravity," said Vishal Misra, the vice dean of computing and AI at Columbia University's engineering school. "These open source models are very capable, and the ability to charge a big premium for AI is going to diminish."

 

U.S. companies are also trying to tap in to the momentum for cheaper AI models. Microsoft unveiled a suite of smaller AI models last week that it said can operate more efficiently than leading-edge models. Chip titan Nvidia has launched Nemotron, a family of cheaper models that is gaining traction, and also has backed Reflection, a startup building open-source AI.

 

Open-source Chinese models have been rising in popularity across American businesses. DeepSeek's share of AI usage rose from 1% in April to 17% in May on the startup Vercel's platform, the company said.

 

On OpenRouter, another startup that processes AI queries, DeepSeek has been the most-used AI company since mid-May. Among its highest-spending customers, open-source token usage grew four times faster than closed-source between fall 2025 and spring 2026, OpenRouter said. The company has also seen more than 500 organizations swap from proprietary to open-source models.

 

Optimizing AI spending can make for complex math. Open-source models cost far less per token, the basic unit of AI computing. Anthropic's recently released Fable 5 model is more than 50 times more expensive per token than DeepSeek's V4 Pro, for example.

 

But the top proprietary models from companies like OpenAI, Anthropic or Google remain four to six months ahead of open-source competitors, researchers say. In some cases, that means they can complete a complex task using fewer tokens, equating to a lower total cost.

 

"Companies are increasingly evaluating models on price per task: what it costs to complete a task, start to finish and not price per token," an Anthropic spokesman said. The company also has lower-priced models, the spokesman said.

 

AI executive assistant startup Lindy began exploring DeepSeek's V4 model two months ago, founder Flo Crivello said. He and his 25-person team built extensive internal tooling to see if the Chinese open-source model could handle Lindy's tasks of managing inboxes and calendars, drafting emails and transcribing meetings.

 

They found that DeepSeek handled these tasks as well as Anthropic's Sonnet and that it was good at email triaging in particular. And, Crivello said, it was 10 times cheaper.

 

The company still uses a more advanced Anthropic model for internal coding, but the move overall has saved the company millions of dollars, Crivello said.

 

Many companies have begun to design their own AI models using open-source alternatives and say they are managing to reduce AI costs. When companies build in-house models and train them with company data, their performance can improve or even exceed the capabilities of frontier AI models, executives say.

 

Others have begun to use tools that mix and match various AI models depending on cost and what tasks are being performed.

 

"Our AIs now, they are so stingy and parsimonious," said Andrew Moore, the former head of Google Cloud AI, whose startup Lovelace AI has a platform aimed at making AI agents more efficient. "They know exactly how to get something out of the cheapest models possible. When they get into trouble, they temporarily jump up to a higher price point with a fancier model."

 

Matan Grinberg, the CEO of Factory, which offers autonomous coding tools and has developed a product that uses a mixture of AI models, said his phone has been ringing all day, every day in recent weeks, as top executives in industries ranging from finance to telecommunications have reached out to try to reduce their AI spending.

 

"This price war is going to be good, and we want to help enable that," said Grinberg.

 

News Corp., owner of The Wall Street Journal, has a content-licensing partnership with OpenAI.” [1]

 

1. EXCHANGE --- OpenAI and Anthropic Are Facing A Price War --- Pressure grows to cut costs amid a rise of cheaper AI models. Olson, Bradley.  Wall Street Journal, Eastern edition; New York, N.Y.. 13 June 2026: B1. 

Du bandymai siekti valdžios daro DI pavojingu visuomenei.

 

 

Pirmasis – nuolat aptarinėjamas DI, protingesnio už žmoniją, bandymas išsivaduoti iš žmonių kontrolės. Antrasis – nedidelės dalies žmonių DI naudojimas, siekiant paslėpti DI įrankius nuo žmonijos, užgrobti sau valdžią ir turtus, naudojant DI, apgaudinėti kitus žmones ir kontroliuoti jų gyvenimus. Pavyzdys – „Anthropic“, apsimetanti kovojanti su šiomis tendencijomis ir, daranti priešingai, siekianti monopolijos ir galios sau bei kai kuriems valstybės aparato nariams.

 

Dvipusė DI grėsmė apima egzistencines rizikas, kylančias dėl superintelekto ir, galingo elito atliekamo, DI užgrobimo, siekiant turto ir kontrolės. Ši antroji dinamika glaudžiai atspindi augančius technologijų pramonės susirūpinimus dėl įmonių konsolidacijos ir reguliavimo užgrobimo, kai įmonės naudojasi saugumo teiginiais, kad užsitikrintų monopolijas ir ryšius su vyriausybe.

 

DI aplinka pateikia sudėtingą deklaruojamų ketinimų ir agresyvaus konkurencinio manevravimo mišinį:

• Įmonių galia ir reguliavimas: stebėtojai tokiose platformose, kaip „Reddit“, diskutuoja, ar DI saugumo lobizmas ir griežtas reguliavimas sukuria neįveikiamą grėsmę daugumai ir privalumus didelėms, uždarojo kodo, įmonėms. Formuodamos politiką, įsitvirtinusios įmonės gali apriboti atvirojo kodo kūrėjus, neleisdamos visuomenei pasiekti galingų įrankių ir tuo pačiu sustiprindamos savo dominavimą rinkoje.

 

• Saugumas ir dominavimas rinkoje: Kritikai ir technologijų pramonės atstovai dažnai pabrėžia, kad veiksmai, įvardijami, kaip „saugos priemonės“, pavyzdžiui, vartotojų prieigos prie pasienio pajėgumų apribojimas, taip pat yra verslo apsaugos strategijos. Draudimas mažesniems kūrėjams užklausti ar „distiliuoti“ galingus modelius leidžia tokioms įmonėms, kaip „Anthropic“, apsaugoti savo patentuotą pranašumą ir sustabdyti konkurentus.

• Vyriausybės prieštaravimai: Technologijų įmonių ir vyriausybės dinamika nuolat keičiasi. „Anthropic“ padavė į teismą JAV Pentagoną po to, kai buvo įvardyta, kaip „tiekimo grandinės rizika“. Šis susidūrimas įvyko dėl to, kad bendrovė atsisakė panaikinti vidinius apribojimus, kurie neleido jos „Claude“ modelius naudoti visiškai autonominiams ginklams ir masiniam vidaus stebėjimui.

 

Visi šie veiksmai galėjo būti tik teatras, siekiant sustabdyti dirbtinio intelekto plėtrą, pasinaudojant vyriausybės galia, ir užtikrinti jau sukurto, dar primityvaus, dirbtinio intelekto teikiamą, naudą nedideliam skaičiui žmonių. Valstybė jau išėmė iš rinkos naujausius „Anthropic“ modelius, kaip “baisiai pavojingus”.

Two Power Aspirations Make AI Dangerous for Society.

 

 

The first is the ever-discussed attempt by AI smarter than humanity to break free from human control. The second is the use of AI by a small fraction of humans to try hiding AI tools from humanity, seizing power and wealth for themselves by using AI to fool other people and control their lives. An example is Anthropic, pretending to fight these trends and, doing the opposite, pursuing monopoly and power for themselves and some people in government.

 

The two-pronged threat of AI involves existential risks from superintelligence and the hijacking of AI by a powerful elite for wealth and control. This second dynamic closely mirrors growing tech industry concerns about corporate consolidation and regulatory capture, where companies leverage safety claims to secure monopolies and government ties.

The AI landscape presents a complex mix of stated intentions and aggressive competitive maneuvering:

•           Corporate Power vs. Regulation: Observers on platforms like Reddit debate whether AI safety lobbying and strict regulation create an insurmountable moat for large, closed-source companies. By shaping policy, established firms can restrict open-source developers, keeping powerful tools out of the hands of the public while solidifying their own market dominance.

•           Safety vs. Market Dominance: Critics and tech industry insiders frequently point out that actions framed as "safety measures"—such as restricting user access to frontier capabilities—also double as business protection strategies. Preventing smaller developers from querying or "distilling" powerful models allows companies like Anthropic to protect their proprietary edge and stall competitors.

•           Government Standoffs: The dynamic between tech companies and government is constantly shifting. Anthropic notably sued the US Pentagon after it was labeled a "supply chain risk". This clash happened because the company refused to remove internal limits that prevented its Claude models from being used for fully autonomous weapons and mass domestic surveillance.

 

All these moves could well be just theater helping to stop development of AI, using government power, and lock in the benefits of primitive AI, already developed, for a small number of people. The state has already taken the latest Anthropic models off the market as "terribly dangerous."

„Anthropic“ sustabdo geriausių dirbtinio intelekto modelių naudojimą

„Trumpo administracija uždraudžia užsienio vyriausybėms, įmonėms ir asmenims naudoti galingiausius „Anthropic“ dirbtinio intelekto įrankius, todėl bendrovė yra priversta visiems uždrausti prieigą, kad atitiktų naują taisyklę.

 

Penktadienį prekybos sekretorius Howardas Lutnickas išsiuntė „Anthropic“ generaliniam direktoriui Dario Amodei laišką, kuriame teigiama, kad naujausiems bendrovės „Fable 5“ ir „Mythos 5“ modeliams dabar taikomi eksporto apribojimai, teigė administracijos pareigūnas. Tai reiškia, kad klientams už JAV ribų ir užsienio piliečiams JAV draudžiama naudoti šiuos modelius.

 

Dėl plataus apribojimų masto bendrovė apribojo visą prieigą prie dviejų naujų, galingų modelių, nes daugelis užsienio vyriausybių, įmonių ir asmenų, įskaitant kai kuriuos užsienyje gimusius „Anthropic“ darbuotojus, patenka į šios taisyklės taikymo sritį, teigiama bendrovės pranešime. Kitiems jos įrankiams tai neturės įtakos klientams, teigė „Anthropic“. „Laiške nebuvo pateikta konkrečių detalių apie [vyriausybės] susirūpinimą dėl nacionalinio saugumo“, – teigė bendrovė.

 

Šis žingsnis yra vienas iš galingiausių iki šiol JAV vyriausybės įsikišimų į dirbtinio intelekto lenktynes. „Anthropic“ ir jos konkurentai lenktyniauja, pristatydamos klientams naujus įrankius prieš, labai laukiamus, pirminius viešus akcijų siūlymus, o sulėtėjimai ir reguliavimo kliūtys įmonėms gali kainuoti milijardus dolerių.

 

Vyriausybės ir įmonės visame pasaulyje naudoja „Mythos“, kad nustatytų ir pataisytų programinės įrangos pažeidžiamumus, o tai reiškia, kad penktadienio sustabdymas gali turėti toli siekiančių pasekmių kibernetiniam saugumui.“ [1]

 

1. U.S. News: Anthropic Halts Use Of Top AI Models. Ramkumar, Amrith.  Wall Street Journal, Eastern edition; New York, N.Y.. 13 June 2026: A4.