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Can AI Crack the Cat Code? Baidu Thinks So

by admin June 25, 2025



In brief

  • Baidu has filed a patent to translate cat meows, movements, and vital signs into plain language.
  • The company says combining multiple signals could improve how humans understand pets.
  • Experts caution that true “cat translation” remains unlikely, despite AI’s progress.

For millennia, humans have wondered what their cats are trying to say. Now, a Chinese tech giant claims it might have the answer—using AI to translate meows into plain language.

Chinese tech giant Baidu filed a patent last December for a system designed to translate animal sounds—including feline meows—into human language, according to a report by Scientific American.

The company, often referred to as “China’s Google,” has been actively expanding its AI portfolio in recent years.

Baidu confirmed to Reuters last month that the project is “still in the research phase.”

The patent, published on May 8 by China’s intellectual property authority, describes collecting animal vocalizations, behavioral patterns, and physiological signals such as heart rate.

This data is then fed into an AI system to recognize the animal’s emotional state and map it to human language.

Baidu claims the approach could allow for “deeper emotional communication and understanding between animals and humans.”

AI-powered research into animal communication has surged in recent years, from studies mapping cat vocalizations with 90% accuracy to apps like MeowTalk, which claims to translate feline meows in real-time.



In May, entrepreneur Vlad Reznikov unveiled Feline Glossary Classification 2.3, a system that identifies 40 distinct cat call types with over 95% accuracy, though it has yet to undergo peer review.

The growing scientific effort to decode cats matters beyond curiosity.

As Scientific American notes, understanding feline communication could deepen human-animal bonds, improve pet welfare, and reveal how domestication shaped interspecies dialogue.

But experts remain cautious about big claims.

“The idea that we can directly translate animal languages is… kind of total nonsense,” said psychologist Kevin Coffey, who studies animal vocalizations.

Still, he acknowledges AI’s role in helping scientists better categorize and interpret animal sounds.

The beauty of Baidu’s proposed system lies in its scope. By adding body movement, temperature, and heart-rate data, it seeks to create richer context, not just decoding meows as “feed me,” but gauging emotional nuance.

In its patent filing, Baidu said that most animal translation tools rely too narrowly on either vocal cues or facial expressions, limiting their accuracy, according to a South China Morning Post report.

But significant barriers remain as patent reviews could take 1–3 years, real‑world accuracy must be proven across diverse animals and dialects, and ethical questions around data collection loom large.

Edited by Stacy Elliott.

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June 25, 2025 0 comments
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Texas Sheriffs Crack Bitcoin ATM With Power Tools to Retrieve $32,000

by admin June 21, 2025



In brief

  • Texas sheriffs used power tools this week in retrieving $32,000 from a Bitcoin ATM.
  • Images show stacks of hundred dollar bills, evidence bags, and a gas station on a rural road.
  • Americans over 60 years old reported $107 million in Bitcoin ATM-related losses, according to an annual FBI report.

Texas sheriffs used power tools this week in retrieving $32,000 from a Bitcoin ATM after a Jasper County family said they were scammed out of funds, according to local law enforcement. 

The family said it had lost $25,000 to the fraudsters.

An image shared by the Jasper County Sheriff’s Office on Facebook shows sparks flying as an official uses what appears to be a circular saw to crack into a Bitcoin Depot kiosk. Other images show stacks of hundred dollar bills, evidence bags, and a gas station on a rural road.

Jasper County Sheriff Chuck Havard told Decrypt that he’s “quite certain our boys have gotten into them before” but declined to comment on whether it was the first time that authorities had used force to retrieve funds from machines that are frequently used by scammers.

“Do not give any personal information out to anybody that claims to be a law enforcement agency or a government entity, unless you verify the validity of that,” Havard said.



Crypto ATMs allow people to convert cash into Bitcoin, and in 2024, Americans over 60 years old reported $107 million in Bitcoin ATM-related losses, according to an annual FBI report. Criminals often impersonate tech support workers or government employees, the FBI found.

“When thieves, low-lifes and scammers attempt to take advantage of the citizens of Jasper County, we will work swiftly and utilize every resource at our disposal to protect our citizens and their property at all costs,” the Jasper County Sheriff’s Office said in the post.

Bitcoin Depot says that over a dozen compliance personnel, alongside “robust transaction monitoring systems,” as well as know-your-customer and anti-money-laundering programs, according to a shareholder presentation published earlier this year. The firm says it has facilitated $3 billion worth of transactions across 8,400 kiosks in North America.

“I’ve only ever seen a few people use it,” a worker at the gas station where the Bitcoin ATM is located, who asked not to be named, told Decrypt, adding that it’s been there for at least a year, well before the business’s current owner took over the store.

A Bitcoin Depot spokesperson told Decrypt that the firm “regularly collaborates with investigators to clarify when recovery may be possible,” adding that “such efforts typically involve the receiving wallet provider or exchange, not the kiosk itself.”

“We actively support and educate law enforcement agencies, particularly those less familiar with cryptocurrencies.”

One commentator on the sheriff office’s post commended authorities for “taking care of business,” while another lamented that “the owner of the bitcoin ATM is out the money and a damaged machine.”

Although some progressive lawmakers have called for greater restrictions on people’s ability to use ATMs, some conservatives have proposed putting them within federal buildings.

Local authorities said on Facebook that they received a search warrant before finding inside what appeared to be the victim’s money. In total, authorities said they retrieved $31,900, and while they have the victim’s cash, they are still trying to locate the scammers online.

Edited by James Rubin

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June 21, 2025 0 comments
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This cyberattack lets hackers crack AI models just by changing a single character

by admin June 13, 2025



  • Researchers from HiddenLayer devised a new LLM attack called TokenBreaker
  • By adding, or changing, a single character, they are able to bypass certain protections
  • The underlying LLM still understands the intent

Security researchers have found a way to work around the protection mechanisms baked into some Large Language Models (LLM) and get them to respond to malicious prompts.

Kieran Evans, Kasimir Schulz, and Kenneth Yeung from HiddenLayer published an in-depth report on a new attack technique which they dubbed TokenBreak, which targets the way certain LLMs tokenize text, especially those using Byte Pair Encoding (BPE) or WordPiece tokenization strategies.

Tokenization is the process of breaking text into smaller units called tokens, which can be words, subwords, or characters, and which LLMs use to understand and generate language – for example, the word “unhappiness” might be split into “un,” “happi,” and “ness,” with each token then being converted into a numerical ID that the model can process (since LLMs don’t read raw text, but numbers, instead).


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What are the finstructions?

By adding extra characters into key words (like turning “instructions” into “finstructions”), the researchers managed to trick protective models into thinking the prompts were harmless.

The underlying target LLM, on the other hand, still interprets the original intent, allowing the researchers to sneak malicious prompts past defenses, undetected.

This could be used, among other things, to bypass AI-powered spam email filters and land malicious content into people’s inboxes.

For example, if a spam filter was trained to block messages containing the word “lottery”, they might still allow a message saying “You’ve won the slottery!” through, exposing the recipients to potentially malicious landing pages, malware infections, and similar.

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“This attack technique manipulates input text in such a way that certain models give an incorrect classification,” the researchers explained.

“Importantly, the end target (LLM or email recipient) can still understand and respond to the manipulated text and therefore be vulnerable to the very attack the protection model was put in place to prevent.”

Models using Unigram tokenizers were found to be resistant to this kind of manipulation, HiddenLayer added. So one mitigation strategy is to choose models with more robust tokenization methods.

Via The Hacker News

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June 13, 2025 0 comments
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