From the perspective of the two major markets of the United States and China, the autonomous driving industry has fallen into a low tide in recent years. For example, last year, Cruise Origin, one of the twin stars of Silicon Valley autonomous driving companies and once valued at more than $30 billion, failed completely, its Robotaxi (driverless taxi) operation qualification was revoked, and autonomous driving models have been discontinued. However, as a new track with the deep integration of digital economy and real economy, automatic driving is a must answer: on the one hand, automatic driving will accelerate the process of technology commercialization and industrialization, and become an important part of the game of major powers; On the other hand, autonomous driving will also promote industrial transformation and upgrading by improving the mass travel service experience, seeking new engines for urban development, and injecting new vitality into the urban economy.

An artificial intelligence (AI) team at Stanford University apologized for plagiarizing a large language model (LLM) from a Chinese AI company, which became a trending topic on the Chinese social media platforms, where it sparked concern among netizens on Tuesday. We apologize to the authors of MiniCPM [the AI model developed by a Chinese company] for any inconvenience that we caused for not doing the full diligence to verify and peer review the novelty of this work, the multimodal AI model Llama3-V's developers wrote in a post on social platform X. The apology came after the team from Stanford University announced Llama3-V on May 29, claiming it had comparable performance to GPT4-V and other models with the capability to train for less than $500. According to media reports, the announcement published by one of the team members quickly received more than 300,000 views. However, some netizens from X found and listed evidence of how the Llama3-V project code was reformatted and similar to MiniCPM-Llama3-V 2.5, an LLM developed by a Chinese technology company, ModelBest, and Tsinghua University. Two team members, Aksh Garg and Siddharth Sharma, reposted a netizen's query and apologized on Monday, while claiming that their role was to promote the model on Medium and X (formerly Twitter), and that they had been unable to contact the member who wrote the code for the project. They looked at recent papers to validate the novelty of the work but had not been informed of or were aware of any of the work by Open Lab for Big Model Base, which was founded by the Natural Language Processing Lab at Tsinghua University and ModelBest, according to their responses. They noted that they have taken all references to Llama3-V down in respect to the original work. In response, Liu Zhiyuan, chief scientist at ModelBest, spoke out on the Chinese social media platform Zhihu, saying that the Llama3-V team failed to comply with open-source protocols for respecting and honoring the achievements of previous researchers, thus seriously undermining the cornerstone of open-source sharing. According to a screenshot leaked online, Li Dahai, CEO of ModelBest, also made a post on his WeChat moment, saying that the two models were verified to have highly similarity in terms of providing answers and even the same errors, and that some relevant data had not yet been released to the public. He said the team hopes that their work will receive more attention and recognition, but not in this way. He also called for an open, cooperative and trusting community environment. Director of the Stanford Artificial Intelligence Laboratory Christopher Manning also responded to Garg's explanation on Sunday, commenting "How not to own your mistakes!" on X. As the incident became a trending topic on Sina Weibo, Chinese netizens commented that academic research should be factual, but the incident also proves that the technology development in China is progressing. Global Times

Google Wallet can help you store your IDs, driving license, loyalty cards, concert tickets and more. You can also store your payment cards and use tap to pay to pay anywhere Google Pay is accepted. Google wallet is available in various countries but Google never launched it in India. Google let indian users stick with the Gpay which facilitates UPI payments. Tap to pay is not part of it. Also we can not store things such as IDs and Passes in indian version of Gpay. This might change and Google may launch Google Wallet in India. With the recent version of Google Wallet and Google Play Services, Google has added some flags and code which indicate that Google is working on something for Indian users regarding wallet. The first change I noticed recently when going through the Google Play Services apk was addition of two new flags Both flags are part of com.google.android.gms.pay package in the Google Play Services. This package contains all the flags for features of Gpay/Wallet. Google does server side flipping of flags to enable/disable features for users. So both these flags doesn't really provide any info about what features enabling these flags is going to bring. But the point here is that Google Wallet is not launched in India so why Google added these flags inside Play Services ? The answer could be that Google may be working on bringing Google Wallet to India. It can enable tap to pay, store payments and various other features for Indian users which we don't have in the current Gpay for India. I found similar flags in the analysis Google Wallet APK - These flags are also disabled by default. But this is again a clear indication of Google working towards something for Indian users. In both cases, enabling the flags doesn't bring anything noticeable UI or feature because there is nothing much added besides flags. Google has dogfood/testing versions internally, so the code will show up slowly in upcoming versions. The last piece of code I found is also from Google Play Services. In case you don't know, Google was working on Digilocker integration in the Google Files app which was supposed to bring your digital document inside the app such as driving license, COVID certificates, aadhar card. But Google has ditched the effort of bringing these features and they removed the "Important" tab (where digilocker was supposed to be integrated) from the Google Files app completely. So things are going to change and here is how. This is the code which I found in the Google Play Services - So the word "PASS" along with PAN, DRIVERS LICENCE, VACC CERTIFICATE & AADHAR CARD, is clear indication of the possibility of Google adding support for these directly through Google Wallet using Digilocker, just like Samsung Pass does it. This code is not old as I have checked older beta versions of Play Services where this code is not present. Here is a string which was added in a previous beta version a few weeks ago but I completely ignored it because it didn't make any sense without flags and the other code - This addition was surprising because there was nothing regarding digilocker before in the Play Services. In the words "pay_valuable", the "pay" to Wallet/Gpay and "valuable" refers to the things like Passes, loyalty cards and transit cards. Since we are talking about digilocker, these "valuable" are driving license, vaccination certificate, PAN card and Aadhar card which can be store in Google Wallet after digilocker integration. That's all about it. We will know more about it in upcoming app updates or maybe Google can itself annouce something about this.

LONDON, July 9 (Reuters) - U.S.-based hedge fund Elliott Associates on Tuesday urged a London court to overturn a verdict supporting the London Metal Exchange's (LME) cancellation of nickel trades partly because the exchange failed to disclose documents. The LME annulled $12 billion in nickel trades in March 2022 when prices shot to records above $100,000 a metric ton in a few hours of chaotic trade. Elliott and market maker Jane Street Global Trading brought a case demanding a combined $472 million in compensation, alleging at a trial in June last year that the 146-year-old exchange had acted unlawfully. London's High Court ruled last November that the LME had the right to cancel the trades because of exceptional circumstances, and was not obligated to consult market players prior to its decision. Lawyers for Elliott told London's Court of Appeal that the LME belatedly released documents in May detailing its "Kill Switch" and "Trade Halt" internal procedures. It also newly disclosed an internal report that Elliott said detailed potential conflicts of interest at the exchange. "It was troubling that one gets disclosure out of the blue in the Court of Appeal for the first time," Elliott lawyer Monica Carss-Frisk told the court. Jane Street Global did not appeal the ruling. "If we had had them (documents) in the proceedings before the divisional court, we may well have sought permission to cross examine." LME lawyers said the new documents were not relevant. "The disclosed documents do not affect the reasoning of the divisional court or the merits of the arguments on appeal," the exchange said in documents prepared for the appeal hearing. "Elliott's appeal is largely a repetition of the arguments which were advanced, and rightly rejected." The LME said it had both the power and a duty to unwind the trades because a record $20 billion in margin calls could have led to at least seven clearing members defaulting, systemic risk and a potential "death spiral". Elliott said the ruling diluted protection provided by the Human Rights Act and also wrongly concluded the LME had the power to cancel the trades.

In fact, ChatGPT can bring more opportunities to many industries, such as customer service, marketing, speech recognition, and more. ChatGPT can help businesses engage with customers more effectively, improve the customer experience, and give businesses more time and resources to focus on other tasks. Come to see While ChatGPT can replace humans in certain situations, it is not a complete replacement for humans. In many cases, human-to-human communication is still the most effective way. Therefore, the emergence of ChatGPT will not lead to the unemployment of all people, but will cause structural changes in the labor force and the redistribution of occupations.