Day: April 1, 2026

Cognichip is building a deep learning model to work alongside engineers as they design new computer chips, News.az reports.
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The problem it is trying to solve is one the industry has lived with for decades: chip design is enormously complex, ruinously expensive, and slow. Advanced chips take three to five years to go from conception to mass production; the design phase alone can take as long as two years before physical layout begins. Consider that the latest line of Nvidia GPUs, Blackwell, contains 104 billion transistors — that’s a lot to line up.
In the time it takes to create a new chip, Cognichip CEO and founder Faraj Aalaei says, the market can change and make all that investment a waste. Aalaei’s goal is to bring the kind of AI tools that software engineers have used to speed their work into the semiconductor design space. 
“These systems have now become intelligent enough that by just guiding them and telling them what the result is that you want, it can actually produce beautiful code,” Aalaei told TechCrunch.
He says the firm’s technology can reduce the cost of chip development by more than 75% and cut the timeline by more than half. 
The company emerged from stealth last year and said Wednesday that it had raised $60 million in new funding led by Seligman Ventures, with notable participation from Intel CEO Lip-Bu Tan, who invested through his venture firm Walden Catalyst Ventures and will be joining Cognichip’s board. Umesh Padval, a managing partner at Seligman, will also join the board. Cognichip has now raised $93 million altogether since its founding in 2024.
Still, Cognichip can’t yet point to a new chip designed with its system and did not disclose any of the customers it says it has been collaborating with since September. 
The company says its advantage is in using its own model trained on chip design data, rather than starting with a general-purpose LLM. That required getting access to domain-specific training data, which is no small feat. Unlike software developers, who share vast amounts of code openly, chip designers guard their IP closely, making the kind of open-source trove that typically trains AI coding assistants largely unavailable.
Cognichip has had to develop its own data sets, including synthetic data, and license data from partners. The firm has also developed procedures to allow chipmakers to securely train Cognichip’s models on their own proprietary data without exposing it.
Where proprietary data isn’t available, Cognichip has leaned on open-source alternatives. In one demo last year, Cognichip invited electrical engineering students at San Jose State University to try the model in a hackathon. The teams were able to use the model to design CPUs based on the RISC-V open-source chip architecture — a freely available design that anyone can build on.
Cognichip is competing against incumbent players like Synopsys and Cadence Design Systems, as well as a well-funded startups like ChipAgentsAI, which closed a $74 million extended Series A in February, and Ricursive, which raised a $300 million Series A round in January.
Padval said that the current flood of capital into AI infrastructure is the largest he’s seen in 40 years of investing.
“If it’s a super cycle for semiconductors and hardware, it’s a super cycle for companies like [Cognichip],” he said.

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The U.S. electric vehicles maker sold 2,920 cars in Italy last month, accounting for a market share of around 1.6%, News.Az reports, citing foreign media.
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In the first three months of this year, Tesla registrations were up 27% compared to the same period of 2025, to 4,419 new vehicles, corresponding to a market share of 0.9%.

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The project, known as BrainWhisperer, is designed to convert brain signals into written language, offering potential new communication pathways for people with speech impairments or paralysis, News.az reports.
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The system has already demonstrated the ability to reconstruct complex sentences from neural signals recorded via intracranial implants.
In one example shared by the company, BrainWhisperer successfully decoded phrases generated purely from brain activity, highlighting the rapid progress of brain-to-text technologies.
A new step in brain-computer interface development
BrainWhisperer forms part of a broader initiative by Tether, described as “Brain OS” – an open-source platform intended to connect brain-computer interfaces with artificial intelligence systems and wearable technologies.
The company says the system is built on top of AI models inspired by Whisper, adapting automatic speech recognition techniques to neural signals rather than audio input.
By converting brain activity into phonemes and then into text, BrainWhisperer aims to reduce word error rates and improve decoding precision across different users and conditions.
Competitive performance and technical benchmarks
Tether reported that its system ranked fourth out of 466 participants in a recent international brain-to-text competition hosted on Kaggle.
According to the company, BrainWhisperer achieved a word error rate of 1.78%, placing it close to the top performers in the field.
The system uses a multi-stage architecture combining several machine learning models, ensemble techniques and phoneme-to-text conversion frameworks to maximise transcription accuracy.
Towards universal decoding across individuals
One of the key challenges in brain-computer interface research is the need to calibrate systems for each individual user – a process that can take hours or even days.
Tether says it is working on “cross-subject” decoding, a method aimed at creating a universal system capable of interpreting neural signals from different individuals without extensive recalibration.
Early results suggest that this approach could significantly reduce setup times while maintaining competitive accuracy compared with existing state-of-the-art models.
Balancing performance and accessibility
Current high-precision systems often rely on invasive brain implants, which require surgical procedures. Tether says it is also exploring non-invasive alternatives, including wearable sensors that can capture signals from the skin or muscles.
These approaches could make brain-to-text technologies more widely accessible, though they face technical challenges such as signal interference and reduced precision.
Implications for healthcare and human-AI interaction
Advances in brain-to-text systems are widely seen as a potential breakthrough for assistive technology, particularly for individuals who are unable to speak or move.
By enabling direct communication from neural signals, such systems could transform how people with severe disabilities interact with the world.
Tether says its long-term goal is to develop systems that allow users to communicate more naturally and efficiently, while maintaining privacy by processing data directly on personal devices.
While independent verification of the latest results is still awaited, the announcement underscores the accelerating pace of innovation at the intersection of neuroscience and artificial intelligence.

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Documents filed after the hearing show Harry was messaging with Mail on Sunday reporter Charlotte Griffiths over about a month from December 2011 to January 2012, News.Az reports, citing foreign media.

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This was before he met his current wife Meghan Markle.

During the hearing Harry had rejected that he had corresponded with the journalist.

But documents filed showed Facebook messages between the pair, with Griffiths calling Harry “Mr Mischief” and him referring to her as “sugar”.

The pair had reportedly met in Ibiza, the party island.

In one message Harry told Griffiths: “I miss our movie snuggles” and signed off a message with “mwah” and strings of kisses.

Griffiths told Harry “what a fun weekend of naughtiness, can’t we all get up to no good in the countryside every weekend damn it, smooches CG String xxx”

Harry then responded that it was “without doubt the best of those weekends I’ve been to.

“Ooh, apparently cinderella’s shoe was found outside that door … sou can relax.please stop panicking!!!! X”.

Earlier, a judge overseeing the lawsuit brought by Prince Harry, singer Elton John and other high-profile figures against ‌the publisher of the Daily Mail at London’s High Court says it will take some time before he can deliver his ruling.

The Duke of ‌Sussex, 41, and six other claimants are suing Associated Newspapers for alleged widespread unlawful activities ranging from hacking voicemail messages, bugging landlines and obtaining private information by deception over more than two decades from the early 1990s.

The publisher ‌rejects their case ‌as ⁠being “preposterous smears”.

During almost 10 weeks of argument, judge Matthew ​Nicklin has heard evidence from the claimants as well as numerous current and former senior journalists from Associated, which also publishes the Mail on Sunday.

David Sherborne, the lawyer for Harry and the other claimants, said there was a culture ⁠at Associated’s titles where its journalists would ‌use ​private investigators to carry out unlawful activities on their behalf.

“Any finding of ​unlawful activity is ‌a disaster,” Sherborne said in his concluding remarks.

The publisher’s lawyer Antony ​White argued that there was no evidence to back up the allegations, the claimants’ witnesses were unreliable and the case against the papers ​was ​scattergun and part of a ​conspiracy by people with a grudge ‌against the press.

“The remaining task is, of course, now mine,” Nicklin said at the end of the trial.

“Judgment will take some time. After a short break over Easter … I will be working on the case and the ​judgment effectively full-time … so I won’t be doing anything else … and I ​will be toiling ⁠away on the judgment.”

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The newly announced sanctions relief represents a strong signal that the U.S. recognizes Rodríguez as a legitimate authority in Venezuela ever since the U.S. military captured Rodríguez’s predecessor, Nicolás Maduro, and his wife on Jan. 3 in Venezuela’s capital, Caracas, News.Az reports, citing foreign media.

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The pair have since been taken to New York to face drug trafficking charges and both have pleaded not guilty.

Venezuela’s government did not immediately respond to a request for comment.

Rodríguez and her brother Jorge Rodríguez were hit with U.S. sanctions during Trump’s first term for their role in allegedly undermining Venezuelan democracy.

The siblings — along with other members of Maduro’s inner circle — were added to the Treasury’s list in September 2018, months after Maduro won re-election in a contest widely considered a sham because opposition politicians and parties were banned from participating.

“Maduro has given Delcy Eloina Rodríguez Gomez and Jorge Jesus Rodríguez Gomez senior positions within the Venezuelan government to help him maintain power and solidify his authoritarian rule,” Treasury said in a statement at the time.

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