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Scientists use AI neural network to translate speech from brain activity
Three recently published studies focused on using artificial intelligence (AI) neural networks to generate audio output from brain signals have shown promising results, namely by producing identifiable sounds up to 80% of the time. Participants in the studies first had their brain signals measured while they were either reading aloud or listening to specific words. All the data was then given to a neural network to “learn” how to interpret brain signals after which the final sounds were reconstructed for listeners to identify. These results represent hopeful prospects for the field of brain-computer interfaces (BCIs), where thought-based communication is quickly moving from the realm of science fiction to reality.
The idea of connecting human brains to computers is far from new. In fact, several relevant milestones have been made in recent years including enabling paralyzed individuals to operate tablet computers with their brain waves. Elon Musk has also famously brought attention to the field with Neuralink, his BCI company that essentially hopes to merge human consciousness with the power of the Internet. As brain-computer interface technology expands and develops new ways to foster communication between brains and machines, studies like these, originally highlighted by Science Magazine, will continue demonstrating the steady march of progress.
In the first study conducted by researchers from Columbia University and Hofstra Northwell School of Medicine, both in New York, five epileptic participants had the brain signals from their auditory cortexes recorded as they listened to stories and numbers being read to them. The signal data was provided to a neural network for analysis which then reconstructed audio files that were accurately identified by participating listeners 75% of the time.
In the second study conducted by a team from the University of Bremen (Germany), Maastricht University (Netherlands), Northwestern University (Illinois), and Virginia Commonwealth University (Virginia), brain signal data was gathered from six patients’ speech planning and motor areas while undergoing tumor surgeries. Each patient read specific words aloud to target the data collected. After the brain data and audio data were given to their neural network for training, the program was given brain signals not included in the training set to recreate audio, the result producing words that were recognizable 40% of the time.
Finally, in a third study by a team at the University of California, San Francisco, three participants with epilepsy read text aloud while brain activity was captured from the speech and motor areas of their brains. The audio generated from their neural network’s analysis of the signal readings was presented to a group of 166 people who were asked to identify the sentences from a multiple choice test – some sentences were identified with 80% accuracy.
While the research presented in these studies shows serious progress towards connecting human brains to computers, there are still a few significant hurdles. For one, the way neuron signal patterns in the brain translate into sounds varies from person to person, so neural networks must be trained on each individual person. The best results require the best data possible, i.e., the most precise neuron signals possible, meaning this is something that can only be obtained by placing electrodes in the brain itself. The opportunities to collect data at this invasive level for research are limited, relying on voluntary participation and approval of experiments.
All three of the studies highlighted demonstrated an ability to reconstruct speech based on neural data in some significant capacity; however, also in all cases, the study participants were able to create audible sounds to use with the computer training set. In the case of patients unable to speak, the level of difficultly in interpreting the brain’s speech signals from other signals will be the biggest challenge. Also, the differences between brain signals during actual speech vs. thinking about speech will complicate matters further.
Elon Musk
Tesla investors will be shocked by Jim Cramer’s latest assessment
Jim Cramer is now speaking positively about Tesla, especially in terms of its Robotaxi performance and its perception as a company.
Tesla investors will be shocked by analyst Jim Cramer’s latest assessment of the company.
When it comes to Tesla analysts, many of them are consistent. The bulls usually stay the bulls, and the bears usually stay the bears. The notable analysts on each side are Dan Ives and Adam Jonas for the bulls, and Gordon Johnson for the bears.
Jim Cramer is one analyst who does not necessarily fit this mold. Cramer, who hosts CNBC’s Mad Money, has switched his opinion on Tesla stock (NASDAQ: TSLA) many times.
He has been bullish, like he was when he said the stock was a “sleeping giant” two years ago, and he has been bearish, like he was when he said there was “nothing magnificent” about the company just a few months ago.
Now, he is back to being a bull.
Cramer’s comments were related to two key points: how NVIDIA CEO Jensen Huang describes Tesla after working closely with the Company through their transactions, and how it is not a car company, as well as the recent launch of the Robotaxi fleet.
Jensen Huang’s Tesla Narrative
Cramer says that the narrative on quarterly and annual deliveries is overblown, and those who continue to worry about Tesla’s performance on that metric are misled.
“It’s not a car company,” he said.
He went on to say that people like Huang speak highly of Tesla, and that should be enough to deter any true skepticism:
“I believe what Musk says cause Musk is working with Jensen and Jensen’s telling me what’s happening on the other side is pretty amazing.”
Tesla self-driving development gets huge compliment from NVIDIA CEO
Robotaxi Launch
Many media outlets are being extremely negative regarding the early rollout of Tesla’s Robotaxi platform in Austin, Texas.
There have been a handful of small issues, but nothing significant. Cramer says that humans make mistakes in vehicles too, yet, when Tesla’s test phase of the Robotaxi does it, it’s front page news and needs to be magnified.
He said:
“Look, I mean, drivers make mistakes all the time. Why should we hold Tesla to a standard where there can be no mistakes?”
It’s refreshing to hear Cramer speak logically about the Robotaxi fleet, as Tesla has taken every measure to ensure there are no mishaps. There are safety monitors in the passenger seat, and the area of travel is limited, confined to a small number of people.
Tesla is still improving and hopes to remove teleoperators and safety monitors slowly, as CEO Elon Musk said more freedom could be granted within one or two months.
News
Tesla launches ultra-fast V4 Superchargers in China for the first time
Tesla has V4 Superchargers rolling out in China for the first time.
Tesla already has nearly 12,000 Supercharger piles across mainland China. However, the company just initiated the rollout of the ultra-fast V4 Superchargers in China for the first time, bringing its quick-charging piles to the country for the first time since their launch last year.
The first batch of V4 Superchargers is now officially up and running in China, the company announced in a post on Chinese social media outlet Weibo today.
The company said in the post:
“The first batch of Tesla V4 Superchargers are online. Covering more service areas, high-speed charging is more convenient, and six-layer powerful protection such as rain and waterproof makes charging very safe. Simultaneously open to non-Tesla vehicles, and other brands of vehicles can also be charged. There are more than 70,000 Tesla Superchargers worldwide. The charging network layout covers 100% of the provincial capitals and municipalities in mainland China. More V4 Superchargers will be put into use across the country. Optimize the charging experience and improve energy replenishment efficiency. Tesla will accompany you to the mountains, rivers, lakes, and seas with pure electricity!”
The first V4 Superchargers Tesla installed in China are available in four cities across the country: Shanghai, Zhejiang, Gansu, and Chongqing.
Credit: Tesla China
Tesla has over 70,000 Superchargers worldwide. It is the most expansive and robust EV charging network in the world. It’s the main reason why so many companies have chosen to adopt Tesla’s charging connector in North America and Europe.
In China, some EVs can use Tesla Superchargers as well.
The V4 Supercharger is capable of charging vehicles at speeds of up to 325kW for vehicles in North America. This equates to over 1,000 miles per hour of charging.
Elon Musk
Elon Musk hints at when Tesla could reduce Safety Monitors from Robotaxi
Tesla could be reducing Safety Monitors from Robotaxi within ‘a month or two,’ CEO Elon Musk says.
Elon Musk hinted at when Tesla could begin reducing Safety Monitors from its Robotaxis. Safety Monitors are Tesla employees who sit in the front passenger seat during the driverless rides, and are there to ensure safety for occupants during the earliest rides.
Tesla launched its Robotaxi fleet in Austin last Sunday, and after eight days, videos and reviews from those who have ridden in the driverless vehicles have shown that the suite is safe, accurate, and well coordinated. However, there have been a few hiccups, but nothing that has put anyone’s safety in danger.
A vast majority — close to all of the rides — at least according to those who have ridden in the Robotaxi, have been performed without any real need for human intervention. We reported on what was the first intervention last week, as a Safety Monitor had to step in and stop the vehicle in a strange interaction with a UPS truck.
Watch the first true Tesla Robotaxi intervention by safety monitor
The Tesla and UPS delivery truck were going for the same street parking space, and the Tesla began to turn into it. The UPS driver parallel parked into the spot, which was much smaller than his truck. It seemed to be more of an instance of human error instead of the Robotaxi making the wrong move. This is something that the driverless cars will have to deal with because humans are aggressive and sometimes make moves they should not.
The Safety Monitors have not been too active in the vehicles. After all, we’ve only seen that single instance of an intervention. There was also an issue with the sun, when the Tesla braked abnormally due to the glare, but this was an instance where the car handled the scenario and proceeded normally.
With the Robotaxi fleet operating impressively, some are wondering when Tesla will begin scaling back both the Safety Monitors and Teleoperators that it is using to ensure safety with these early rides.
CEO Elon Musk answered the inquiry by stating, “As soon as we feel it is safe to do so. Probably within a month or two.”
As soon as we feel it is safe to do so.
Probably within a month or two. We continue to improve the Tesla AI with each mile driven.
— Elon Musk (@elonmusk) June 30, 2025
Musk’s response seems to confirm that there will be fewer Teleoperators and Safety Monitors in the coming months, but there will still be some within the fleet to ensure safety. Eventually, that number will get to zero.
Reaching a point where Tesla’s Robotaxi is driverless will be another significant milestone for the company and its path to fully autonomous ride-sharing.
Eventually, Tesla will roll out these capabilities to consumer-owned vehicles, offering them a path to generate revenue as their car operates autonomously and completes rides.
For now, Tesla is focusing on perfecting the area of Austin where it is currently offering driverless rides for just $4.20 to a small group of people.
Tesla investors will be shocked by Jim Cramer’s latest assessment
Tesla launches ultra-fast V4 Superchargers in China for the first time
Elon Musk hints at when Tesla could reduce Safety Monitors from Robotaxi
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