TH

AIエンジニア → セキュリティエンジニア | アニメ鑑賞、サッカー観戦、投資が趣味の20代 | 米国株トレーダー | 東京都在住 | どっかのJサポ | ツイートは主の心の声であり、組織と全く関係ありません。

[TH @tomatomah23]

$PLTR 新高値更新おめでとう
ガチホしていてよかった

[SOU⚡️投資ニュース / 米国株・日本株・仮想通貨・AI @SOU_BTC]

🇺🇸 米国防総省にも不正アクセス　個人情報300万人分が平文で漏えいか……発覚までに9カ月

米国では連邦捜査局（FBI）もサイバー攻撃を受け、捜査官らの個人情報が流出したと伝えられたばかりだった。確実なセキュリティ対策を講じているはずの米政府機関で相次いだ事態に、関係者は衝撃を受けている。

[じじちゃん @sourenhou]

学園HUNTER×HUNTER　②

[TH @tomatomah23]

openaiが起点の暴落っぽい

[Wall St Engine @wallstengine]

OPENAI'S ANNUALIZED REVENUE NEARS $50B, BELOW EARLIER $70B REPORTS: FT

OpenAI recently told investors its annualized revenue was approaching $50B at the end of September, roughly $20B below the figure widely reported last month.

The discrepancy reportedly stems from differences in how OpenAI and Anthropic calculate revenue. Anthropic includes sales through cloud partners such as AWS and Google Cloud, while OpenAI does not.

Investors had attempted to adjust OpenAI's figures to make them comparable with Anthropic's, contributing to the previously reported $70B estimate.

OpenAI declined to comment.

Source: Financial Times.

[SOU⚡️投資ニュース / 米国株・日本株・仮想通貨・AI @SOU_BTC]

【速報】🇺🇸 OpenAIの年換算売上高は、従来示していた水準を200億ドル下回る：英フィナンシャル・タイムズ

[TH @tomatomah23]

うぉー、株なんかヤバい下落してる（笑）

[TH @tomatomah23]

わいのポートフォリオ大半のパランティアが火を吹いておる

[WOLF @WOLF_Financial]

Goldman Sachs upgraded Palantir $PLTR to Buy, saying its moat is likely to drive another step-function change in its addressable market.

[TH @tomatomah23]

インフルのワクチン打った！
これで、インフルかからなければいいな～

[TH @tomatomah23]

インフルのワクチン接種そろそろ行ったほうがよさそう

[SOU⚡️投資ニュース / 米国株・日本株・仮想通貨・AI @SOU_BTC]

【速報】🚨 Anthropic、売上12倍も巨額赤字

AnthropicのIPO目論見書で、急成長の一方で巨額のコスト負担が明らかに。

・2025年度売上高：45.9億ドル
→ 前年比 +1,088%

・営業損失：80.6億ドル
→ 前年の29.8億ドルから大幅拡大

・純損失：419.7億ドル
→ 前年は83.1億ドル

・AI計算・インフラ費：73.3億ドル
→ 前年比 +190%
→ 営業費用の58%

・現金・短期投資：202.8億ドル

さらに、売上の24%を上位2社の顧客に依存。

売上は爆発的に伸びている一方、AI開発競争のコストも桁違いになっている。

[NIK @ns123abc]

🚨BREAKING: Claude is officially a NATIONAL SECURITY THREAT and is BLACKLISTED from the ENTIRE defense supply chain

>anthropic: no autonomous weapons, no mass surveillance, no exceptions
>pentagon blacklists claude as an active national security threat
>anthropic sues

Federal court ruled 2–1 AGAINST Anthropic:

"As Anthropic admits, the company encodes restrictions into Claude that prevent the model from performing tasks that Anthropic wishes to prevent."

"On more than one occasion, these restrictions have stopped Claude from performing tasks requested by government users":

>refused to perform "tasks that were appropriate in a national security context"
>refused CDC queries on infectious disease prevention research
>anthropic questioned claude's use in the military operations

"Anthropic's Chief Science Officer explained how the company 'seek[s] to embed safety considerations directly into the model itself.'"

"[Anthropic's] CEO explained how such training gives the model an 'identity, character, values, and personality' of its own, tethered to a 'constitution' developed to impose 'high-level principles and values' on Claude itself."

"We have no reason to doubt that Anthropic manipulates Claude's function with noble intentions... BUT the statutory definition of a 'supply chain risk' turns on what Anthropic does, not why Anthropic does it."

"In our Republic, it is the President and the Secretary of War who must determine how best to balance the competing risks. In doing so here, the Secretary DID NOT transgress any limits on his authority."

ITS OVER.
ANTHROPIC IPO IN SHAMBLES

[Wall St Engine @wallstengine]

ORACLE SEEKS PROTECTION FROM DATA CENTER DELAYS

$ORCL has issued a force majeure notice tied to Project Jupiter, the 2.45GW New Mexico data center that is part of the Stargate AI buildout, Bloomberg reports.

Oracle is not trying to exit the project, but is seeking to delay payments if the site misses its planned 2028 opening.

The project has faced permitting setbacks, including a six-month delay to a key gas pipeline. Its $18B construction debt is already trading below 90 cents on the dollar.

Oracle says the project remains on schedule.

[Dario Amodei @DarioAmodei]

Today we announced the Claude-led discovery of a molecular machine that we suspect could represent a new gene editing mechanism. Its precise function, biotechnological utility (if any), or level of significance is not yet clear, but at minimum it is work I would have been proud to do as a PhD student. The work was done mostly, though not entirely, by Claude: our life sciences team suggested a broad area of research, Claude read through the literature and a bunch of genome data and discovered something interesting, then Claude proposed experiments to verify the discovery and our team carried them out.

It’s easy to dismiss this as a one-off or curiosity, but we’ve repeatedly seen a pattern where AI performance in new intellectual domains goes from weak to superhuman in a matter of a few years. In 2023 models struggled to do math at the level of an average high-school student. In 2024 they started to do well on math competitions for the best high-schoolers in the country, in 2025 they started to solve minor open problems, in early 2026 more significant open problems, and in late 2026 they are beginning to solve the top few open problems in all of mathematics. We believe AI for biology is on a similar exponential trend.

The main difference between biology and mathematics, of course, is that math can be done purely theoretically, while biology requires experimentation. Some have used this to draw the conclusion that AI’s utility in biology will be limited. We think this is wrong. As we’ve demonstrated today, humans can collaborate with AI to perform the experiments, validate key results in a few weeks and, if necessary, work with the AI to iterate on what they find. Eventually it may even be possible for Claude itself to safely perform the experiments by autonomously controlling lab equipment, with appropriate safeguards in place, but we aren’t doing that today (our lab is also a BSL1/BSL2 facility that doesn't handle materials dangerous to humans).

More broadly, biomedical advancement has many stages — from fundamental biology discoveries, to translational research, to drug discovery, clinical trials, and finally the actual delivery of medicines and health care to patients. We are also interested in these later stages, but even simply accelerating the first stage of fundamental biological discoveries has the potential to speed up and broaden the entire pipeline. Improving our understanding of biology and sharpening biologists’ tools can drive forward all of the later stages, for example by identifying new drug targets, finding new therapeutic modalities, allowing for more precise measurement, and speeding up the experimental loop which itself further accelerates our understanding of biology. This will not in itself speed up clinical trial times, but if it succeeds it could greatly increase the number of promising candidates that go into the pipeline — an increase in throughput even though latency remains.

In Machines of Loving Grace, I wrote about AI’s potential to “cure most diseases in 5-10 years” — a goal that sounds impossible, but one I believe is just barely possible if AI is applied to every stage of the pipeline. The first step is showing that AI can first help with, and then drive, biological discoveries.

Claude’s discovery is the latest in a line of related prior work that goes back decades, beginning with systems like CRISPR, and continuing with discoveries like the bridge recombinase and VIPR in the past few years. Recently, there has been heightened interest in systems based on reverse transcriptase (RT) enzymes, the enzyme underlying the system Claude identified. And most recently, a Stanford team working independently described a novel RT system with an associated non-coding array that is in some ways similar to the one Claude found, though they are distinct systems that evolved independently from each other. I believe that we’re at the very beginning of finding such systems and developing them into powerful tools for biotechnology.

I’m proud of the resources Anthropic has invested in accelerating the public benefits of AI through the life sciences, and we’re aiming both to grow our life sciences team and to work with other scientists to extend this approach to a broad range of problems. If you have a proposal for a research collaboration or are interested in joining our life sciences team, please reach out.

[TH @tomatomah23]

シーリングライト寿命で２日間暗闇の中過ごしていたが、交換してやっと部屋が明るくなった！快適！

[みんなのFX｜トレイダーズ証券【公式】 @Min_FX]

【要人発言】
🇺🇸トランプ大統領
「戦争を終わらせたい」

[TH @tomatomah23]

直近もう一回ドンパチありそうだから、 $RTX 買いな気がしてきた

[HAHI @1234hahi]

抜けなくなっちゃった、、、