One of the obstacles in creating a quantum computer is the inability to control many qubits at the same time.
Quantum Physics Specialists at the University of Copenhagen made a huge step forward in the field of quantum technology, finding a way to bypass the main obstacle to the creation of a quantum computer. In particular, the researchers managed to simultaneously control several spin qubits on a single quantum chip.
One of the main obstacles in creating a large functional quantum computer is the impossibility of simultaneously controlling many basic memory devices (qubits). Controlling one qubit usually negatively affects another due to the simultaneous action of control pulses.
Unlike companies like Google and IBM that are working on superconducting technology for quantum processors, researchers have focused on semiconductor, or so-called spin, qubits.
In general terms, spin qubits are made up of electron spins trapped in semiconductor nanostructures called quantum dots, so that individual spin states can be controlled and entangled with each other, the researchers explained.
Spin qubits can maintain their quantum states for a long time, which potentially allows them to perform faster and more accurate computations compared to other types of platforms. Since spin qubits are very small, there are a lot of them on a single chip. This is important because the more qubits, the more processing power.
The researchers were able to create and manipulate four qubits on a single chip with 2×2 rows. One of their main tasks was to get the qubits to communicate with each other.
“Now that we have good qubits, we need to combine them into a circuit capable of driving many qubits, but at the same time complex enough to correct the errors of quantum computation. 2 × 2 and 3 × 3 qubits. The problem is that you can only control one qubit at a time, “the researchers explained.
The researchers created a quantum circuit made of a semiconductor substance called gallium arsenide, and its size does not exceed the size of a microbe. However, the main thing is that the chip allowed experts to control and measure all qubits at the same time.
In quantum computing, it is very important to control and measure simultaneously. Qubits are very sensitive, and if measured one by one, even tiny ambient noise can disrupt quantum information on the system.
Another significant obstacle is that all 48 control electrodes on the chip have to be manually tuned and kept tuned. It takes a long time for humans, so specialists are looking for ways to use optimization algorithms and machine learning to automate this process.
Hackers hacked Tesla twice, for which they received 350 thousand dollars and Tesla Model 3
As part of Pwn2Own’s Vancouver-based commercial vulnerability finding event, a French team called Synacktiv managed to hack into Tesla systems twice.
On the first day, Synacktiv successfully performed a TOCTOU (Time-of-check to time-of-use) attack on the Tesla Gateway, and the group was rewarded with a $100,000 cash reward and a Tesla Model 3 car. And the next day hackers broke into the Tesla infotainment system, and received another 250 thousand dollars for this.
The Tesla cybersecurity team is already analyzing the actions of hackers in order to eliminate the vulnerabilities found with a firmware update.
Scissors undercut: Windows 11 vulnerability reveals sensitive information from screenshots, including deleted parts
A dangerous vulnerability has been discovered in one of the standard Windows 11 applications that could lead to the disclosure of sensitive information to the user. Moreover, at the moment the vulnerability is not closed and attackers can use it.
We are talking about the application Snipping Tool (Scissors). The vulnerability, called aCropalypse, allows you to undo changes made by a user when editing a screenshot, including cropped or blurred parts that hide sensitive data.
When you edit a screenshot, you can save it with the same name as the original file by overwriting it. However, as it turns out, the Windows 11 Snipping Tool does not remove the original information from the file, but simply leaves it added at the end, which is usually invisible to users. With some trickery, a potential attacker can extract hidden information from a file and see what information has been edited.
As you can see, edited screenshots are usually much larger due to the inclusion of information from the original image.
This is a pretty serious vulnerability. For example, if you share a screenshot of an order confirmation page on Amazon, it may contain an address, the same goes for credit card numbers and other sensitive data.
In 2018, Google had an AI ready for a ChatGPT-style chatbot, but it was closed due to security issues.
In recent months, the ChatGPT chatbot has been on the news pages, and this has forced many companies to catch up with OpenAI. Among them are Microsoft, Google and a number of Chinese corporations. However, reportedly, the situation could be different.
As early as 2018, Google is said to have had a natural language processing AI similar to ChatGPT. However, company executives closed the project, considering it too dangerous. One of the developers was research engineer Daniel De Freitas, and Noam Shazeer, a software engineer at Google, also contributed to the project.
The project was called Meena and was a chatbot that could talk about different topics. With him you could discuss TV shows, have discussions about philosophy and joke. At the same time, the developers believed that this technology could be added to the search engine, however, in the end, Google stopped development. The company said the bot did not meet its AI security standards.
Note that later, on the basis of these developments, the LaMDA chat bot was created, which flies into the basis of Bard. Thus, the development nevertheless reached the mass user, albeit with a great delay.
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