Remittances Remittances. What is so easily overlooked as more and more immigrants choose Ireland to take up residence. We need accountability about what is remitted back home. Worth knowing £6 is a monthly wage in Sudan!

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Futurism: Anthropic Just Sent Shockwave … Release of a New AI Tool

Anthropic Just Sent Shockwaves Through the Entire Stock Market by Releasing a New AI Tool

A minor update with major consequences.

By Frank Landymore

Published Feb 5, 2026 9:01 AM EST

Anthropic CEO Dario Amodei is shown with curly dark hair and glasses is wearing a dark pinstripe suit jacket over a white shirt. He has a slightly open mouth expression. The background is a green grid pattern with an orange circle behind his head.
Illustration by Tag Hartman-Simkins / Futurism. Source: Michael M. Santiago / Getty Images

Last week, Anthropic released a new AI tool for automating legal work, precipitating a mass stock market selloff over fears that the tech could upend huge software customers in industries ranging from law to finance, Reuters reports — an urgent example of the power that AI currently has over financial markets and even the economy writ large.

The S&P 500 software and services index fell by nearly nine percent over five trading sessions, and is down over 20 percent from its October peak following the release of the AI tool. The Nasdaq 100 Index is similarly despondent, down by around 2.6 percent.

Thomson Reuters, Reuters’ parent company which operates a large legal division, saw its stock plunge by over 20 percent over five days. Both the SaaS heavyweight Salesforce and the global cloud-based cybersecurity firm Crowdstrike fell by around percent, but eased on Wednesday.

The stock rout is a sign of the tense fears over AI automation’s potential to disrupt entire industries and especially those focused on knowledge work — despite the tech’s still considerable shortcomings.

“We are not yet at the point where AI agents will destroy software companies, especially given concerns around security, data ownership and use,” Ben Barringer, head of technology research at Quilter Cheviot, told Reuters,

The buzz centers on a new plugin for Anthropic’s Claude Cowork AI agent, which was released last month. Simply titled “Legal,” Anthropic says it can speed up and even automate contract review, non-disclosure agreement triage, and compliance workflows — “all configurable to your organization’s playbook and risk tolerances.” Of course, none of what it produces should be construed as legal advice: “All outputs should be reviewed by licensed attorneys,” Anthropic cautions.

Nonetheless, this was taken as bad news for legal divisions everywhere, the shockwaves of which were felt in the larger market. Morgan Stanley analysts summarized the anxieties in a note to Thomson Reuters: “Anthropic launched new capabilities for its Cowork to the legal space, heightening competition,” they wrote. “We view this as a sign of intensifying competition, and thus a potential negative.”

There’s still considerable doubt over the efficacy of AI agents in the workplace. A MIT study found that companies which integrated AI into its workflows saw no meaningful increase in revenue, while analysts have observed that the tools haven’t led to a bump in productivity, either. Its introduction into the legal sphere has been particularly fraught, with numerous lawyers landing in hot water with a judge after their AI tools incorrectly cited sources and fabricated caselaw. Perhaps AI agents will find some general purpose use among white collar workers, but there’s a long way to go before they can have a sniff at highly specialized fields.

“It feels like an illogical leap to extrapolate Claude Cowork Plugins, or any similar personal productivity tools, to an expectation that every company will hereby write and maintain a bespoke product to replace every layer of mission-critical enterprise software they have ever deployed,” JP Morgan analyst Mark Murphy told Reuters.

Even so, it’s undeniable that AI has the market feeling pretty jumpy.

More on AI: Tech Companies Showing Signs of Distress as They Run Out of Money for AI Infrastructure

Frank Landymore

Contributing Writer

I’m a tech and science correspondent for Futurism, where I’m particularly interested in astrophysics, the business and ethics of artificial intelligence and automation, and the environment.

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President Trump: WE NEED A NEW NUCLEAR TREATY

TRUMP: WE NEED A NEW NUCLEAR TREATY “Rather than extend ‘NEW START’ (A badly negotiated deal by the United States that, aside from everything else, is being grossly violated), we should have our Nuclear Experts work on a new, improved, and modernized Treaty that can last long into the future.” I agree. China is developing more nuclear weapons than the rest of the world combined, and any treaty MUST include them! Source: Truth Social

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Einstein: Wise words

Physics In History
@PhysInHistory

A hundred times every day I remind myself that my inner and outer life are based on the labors of other men, living and dead, and that I must exert myself in order to give in the same measure as I have received and am still receiving.

— A. Einstein (1879-1955)

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Elon Musk “I think colleges are basically for fun…You literally just need the phone, internet and Grok to learn../

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Financial Times: Files released by the US justice department indicate that Andrew Mountbatten-Windsor sought to encourage an Emirati foreign minister to do business with Jeffrey Epstein in 2010.

Financial Times

@FT

Files released by the US justice department indicate that Andrew Mountbatten-Windsor sought to encourage an Emirati foreign minister to do business with Jeffrey Epstein in 2010. https://ft.trib.al/khrb0rM

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President Trump: Europe has big problems

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Lizz Truss interview on X. Often said there are so many good people found in the NHS but “there are also a lot of lazy people”

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Elon Musk … The National Debt

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The Harvard Gazette: New AI tool predicts brain age and more…

New AI tool predicts brain age, dementia risk, cancer survival 

Close up of robotic hand pointing and clicking at brain holographic to access medical data or diagnosis symptom.

Mass General Brigham Communications

February 5, 2026 3 min read

Unlike other AI models, BrainIAC needs limited data to ID key neurological health indicators

A new AI foundation model has been developed that can accurately extract multiple disease risk signals from routine brain MRIs, including: estimating a person’s “brain age”; predicting dementia risk; detecting brain tumor mutations; and predicting survival from brain cancer, according to investigators from Harvard-affiliated Mass General Brigham.

The model, a brain imaging adaptive core called BrainIAC, was trained on nearly 49,000 brain MRI scans. The tool outperformed other, more task-specific AI models, and was especially efficient when limited training data were available. 

Results are published in Nature Neuroscience.

According to researchers, despite recent advances in medical AI approaches, there is a lack of publicly available models that focus on broad, brain MRI analysis. Most conventional frameworks perform specific tasks and require extensive training with large, annotated datasets that can be hard to obtain. Furthermore, brain MRI images from different institutions can vary in appearance and based on their intended applications (such as in neurology versus oncology care), making it challenging for AI frameworks to learn similar information from them.

To address these limitations, BrainIAC uses a method called self-supervised learning to identify inherent features from unlabeled datasets, which can then be adapted to a range of applications. After pretraining the framework on multiple brain MRI imaging datasets, the researchers validated its performance on 48,965 diverse brain MRI scans across seven distinct tasks of varying clinical complexity.

Researchers found that BrainIAC could successfully generalize its learnings across healthy and abnormal images and subsequently apply them to both relatively straightforward tasks, such as classifying MRI scan types, and very challenging tasks, such as detecting brain tumor mutation types. The model also outperformed three more conventional, task-specific AI frameworks at these applications and others.

The authors note that BrainIAC was especially good at predicting outcomes when training data was scarce or task complexity was high, suggesting that the model could adapt well to real-world settings where annotated medical datasets are not always readily available. Further research is needed to test this framework on additional brain imaging methods and larger datasets.

“BrainIAC has the potential to accelerate biomarker discovery, enhance diagnostic tools, and speed the adoption of AI in clinical practice,” said corresponding author Benjamin Kann of the Artificial Intelligence in Medicine (AIM) Program at MGB and associate professor of radiation oncology at Harvard Medical School. “Integrating BrainIAC into imaging protocols could help clinicians better personalize and improve patient care.”


This study was supported in part by the National Institutes of Health/the National Cancer Institute and Botha-Chan Low Grade Glioma Consortium.

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