South Korea has levied tens of millions of dollars in fines on Alphabet’s (GOOGL.O) Google and Meta Platforms (META.O) for privacy law violations, authorities said on Wednesday. The Personal Information Protection Commission (PIPC) said it fined Google 69.2 billion won ($50 million) and Meta 30.8 billion won ($22 million).
The privacy panel said that the firms did not inform service users and obtain their prior consent when collecting and analyzing behavioral information to infer their interests or use them for customized advertisements. A Google spokesperson said they disagree with the PIPC’s findings and will review the entire written decision once it is shared.
The spokesperson said that Google has consistently demonstrated its commitment to releasing ongoing updates that provide users control and transparency while facilitating the most helpful products possible. They added that Google would remain committed to engaging with the PIPC to protect the privacy of South Korean users.
A Meta spokesperson said that while the company respects the commission’s decision, they are confident that they work with their clients in a legally compliant way that meets the processes required by local regulations. Further, they said that Meta disagrees with the commission’s decision and will be open to seeking a ruling from the court.
Also, on Wednesday, Google suffered its second setback in Europe in less than a year as the top court agreed with EU antitrust regulators that it had abused its dominance. Google lost its challenge to a 2.42 billion euro ($2.42 billion) fine the previous year, though the EU Court of Justice did trim it slightly.
Adani Group has partnered with Prisma AI at the Sardar Vallabhbhai Patel International Airport (SVPIA) in Ahmedabad to rollout visual AI technology on airports. Prisma AI is a visual-AI-based company majoring in predictive information technologies using a computer vision platform. The airport, including five other airports, is being operated by Adani Airports.
With Prisma AI’s Visual AI technology, all the airports belonging to the Adani Group will have cutting-edge visual technology to deliver an immersive airport experience catering to the growing customer base and footfall at the airport. The partnership and the Visual AI technology provided by Prisma AI will enhance customer experience and give Adani Group an edge in the industry.
At present, the service has been deployed at the SVPIA at the departure area of the domestic terminal (T1), covering departure and pre-security areas. However, the technology named “Desk of Goodness system” is being implemented in all six Adani Airports and will be available soon.
With Prisma AI technology, Adani Group has adapted Visual AI to provide humanitarian assistance to the customers at the Airports. “Desk of Goodness” strives to assist passengers such as older persons, women with infants, and those in need of a wheelchair and assistance.
In addition, the technology recognizes incidents such as a fall or unusual passenger behavior. This desk is staffed by goodness champions equipped with smart tablets that keep them informed in real-time where travelers want assistance so they can rush to them. This proactive mode of real-time support process is achieved by utilizing Prisma AI’s patented Visual AI algorithms.
On Tuesday, most of the Twitter (TWTR) shareholders voted in favor of Musk’s $44 billion takeover deal, a value of $54.20 per share. The company’s stock opened Tuesday at under $41 per share, nearly 25% below the deal price. A preliminary count showed that 98.6% of the votes favor the deal, said Twitter.
The vote came days after Elon Musk’s third letter to Twitter, asking to terminate their deal, with this one attached to a purported $7.75 million severance payment the company initiated to its former head of security, Peiter Zatko, who later warned about its alleged security and privacy vulnerabilities.
In the letter, Musk’s attorneys claimed the payment was made to Zatko and his lawyers on June 28 as part of a separation contract that violated a provision of the acquisition contract. According to the contract, Twitter agreed not to give any severance payments to employees in amounts outside the ordinary track of business consistent with past practice. Twitter slammed Musk’s latest efforts to get out of the deal as invalid and wrongful.
Musk sent the first letter to terminate the deal in the month of July, alleging that Twitter violated the agreement by misrepresenting the figures of spam and fake bot accounts on its platform. Twitter sued Elon Musk to complete the acquisition, accusing the billionaire of using bots as a pretext to exit a deal he developed over buyer’s remorse following a market decline.
Zatko testified at the US Senate on Tuesday about what he alleged are Twitter’s strict security and privacy vulnerabilities, including possibly having foreign intelligence agents on its payroll. The case between Musk and Twitter is scheduled to go to trial on October 17.
The new Vedanta-Foxconn semiconductor plant will be set up in Gujarat, announced Anil Agrawal, CEO of Vedanta Resources Limited. Vedanta’s investment of ₹1.54 lakh crores will help make India’s independent Silicon Valley a reality, said Agrawal in a tweet.
History gets made! 🇮🇳 Happy to announce that the new Vedanta-Foxconn semiconductor plant will be set up in #Gujarat. Vedanta’s landmark investment of ₹1.54 lakh crores will help make India's #Atmanirbhar Silicon Valley a reality. (1/4)
Vedanta obtained financial and non-financial subsidies, including capital expenditure and cheap electricity from Gujarat to build the semiconductor plants. The project will include display and semiconductor facilities near the largest city of Ahmedabad in the western state.
While soliciting incentives, Vedanta had sought 1,000 acres (405 hectares) of land free of cost on a 99-year lease and water and power at concessionary and fixed prices for 20 years.
Agrawal added that the project would help fulfill PM Narendra Modi’s vision of creating a robust manufacturing base in India. It will also reduce India’s electronics imports and provide 1 lakh direct skilled jobs to Indians, turning them from employees to employers.
Agrawal expressed his gratitude to the Gujarat government and the Union IT Minister for helping Vedanta tie things up quickly. He said that India’s tech ecosystem would thrive, benefiting every state from the new manufacturing hubs for electronics.
India will fulfill the digital needs of not just its people but also those from across the seas, said Agrawal. Vedanta Resources Limited, an oil-to-metals conglomerate, decided to diversify into chip manufacturing in February and formed a joint venture with Foxconn.
Recently, the Japanese government honored seven mayors for their dedicated efforts in developing innovations and concepts for their towns’ digital economies. As a result, the Japanese government is now among the first to award nonfungible tokens (NFTs) as an extra incentive for the efforts of local authorities that have succeeded at utilizing digital technology to address local problems.
The mayor of Sakata, Yamagata Prefecture, who recently proposed using electric cars for local delivery, was one of the honorees. Another winner of the NFT award is Maebashi in the Gunma Prefecture, who came up with the idea for a platform that would employ mobile devices’ cameras to track changes in traffic conditions in real-time.
The honors were granted during the “Summer Digi Denkoshien 2022” ceremony by the Cabinet Secretariat, a department of the government overseen by the nation’s Chief Cabinet Secretary, Hirokazu Matsuno. Fumio Kishida, the nation’s prime minister, also attended the event.
These Ethereum-based proof-of-attendance protocol (POAP) NFTs were issued through Hazama Base. Due to the assets’ lack of transferability, they cannot be sold on the secondary market. According to sources, the platform seems quite popular with the Japanese government. In other words, this is not the first time the network has been utilized to issue NFTs. At a previous event held by the Liberal Democratic Party Youth Bureau, NFTs were also issued and distributed via the Hazama Base platform.
The Summer Digi Denkoshien 2022 event was sponsored by four companies: IndieSquare, bitFlyer Holdings, TREE Digital Studio, and Tomonari Kougei.
Meta Platforms led a sharp turn lower in social-media stocks Tuesday after the consumer-price index unexpectedly moved higher during August, with continuing inflation reigniting fears of a pullback in online advertising.
Shares of the Facebook parent company fell 9.4% Tuesday, their worst day since February 3, amid broad declines for U.S. stocks, particularly for big tech names. The Nasdaq Composite Index COMP fell 633 points or 5.2%.
According to Dow Jones Market Data, Meta’s META stock closed Tuesday at $153.13, its lowest level since March 23, 2020. If the stock were to finish a session lower than $146.01, it would officially wipe out all of its pandemic-era gains.
Other social-media names also fell sharply, including Snap Inc. SNAP, off 7%, and Pinterest Inc. PINS, down 4.3%. Ad-dependent Alphabet Inc. GOOG GOOGL, which runs the YouTube platform and the Google suite of services, slipped 5.9%.
Meta and its social-media peers have been on a rocky ride this year amid concerns about the impacts of inflation and other economic challenges on advertiser activity. The company logged its first-ever year-over-year drop in revenue during the June quarter, with executives saying they expected overall effects on the advertising business and planned to cut costs given the climate.
Despite jitters about the advertising industry, payment-technology companies have indicated that spending remains strong, even if consumer confidence is pressured.
Most existing language models are built and trained to provide textual outputs based on the initial inputs. These models efficiently output texts but are restricted to providing only left-to-right language modeling results by predicting the next word. They are not trained to perform specific tasks during the entire writing process, like updating existing texts (even the ones generated by them) and editing. Besides, conventional models are tough to control and cannot explain their actions. Consequently, they are insufficient for collaborative writing.
To address the insufficiencies, Meta AI Research is introducing PEER, a language model extended to enhance collaborative writing techniques by fragmenting a task into smaller subtasks. The PEER or Plan, Edit, Explain, and Repeat model is trained for the entire writing process, not just the final output. It can plan drafts, give suggestions, overlook edits, and explain editing actions, offering several upsides over the standard left-to-right language models.
You need a proper dataset with an accessible history of edits for training a language model for multiple subtasks like the ones done by PEER. This is because the capability to suggest and explain edits sets PEER apart from other models. It is challenging to obtain edit histories via standard web crawls for most data sources, leading to data scarcity.
To overcome data scarcity, Meta has trained the model on Wikipedia edits to infill PEER with all processes and edit histories, making it applicable to several public domains for which edit histories are unavailable. Wikipedia provides a complete editing history with comments and citations on a large scale.
While Wikipedia solves the data scarcity problem, it poses a few others, like noisy comments, lack of citations, and high specificity of data to Wikipedia’s textual content and edits. Meta has trained multiple PEER instances, not just one, to solve the above problems by generating synthetic data as a proxy for missing pieces. This synthetic data also replaces low-grade sections in the existing data.
The model’s core idea is to explain textual content editing as an iterative process that is repeated till the desired output is received. Let’s say you have a text sequence xₜ, a plan Pₜ, and a set of documents Dₜ containing necessary information. Based on xₜ, Pₜ and Dₜ, you can create a planPₜ₊₁ to give instructions about further modifications, like “fix spelling errors,” “simplify,” etc. After planning, the model repeats iterations wherein each iteration edits the text to give an updated version xₜ₊₁. Lastly, the model explains the intentions behind the edits via a textual explanation, eₜ, based on (xₜ, xₜ₊₁, and Dₜ).
The entire process of planning, editing, and explainingis repeated numerous times to obtain a sequence of xₜ, xₜ₊₁, xₜ₊₂, and so on till any xₙ is the same as xₙ₋₁, or there are no more edits.
Each step makes PEER highly relevant to collaborative writing, where dividing the entire process into phases enhances the quality and worthiness of the output. The explanation and planning phases might be similar given that the model explains what you (or the model) planned; the difference is when they happen. Planning happens before the model edits and explanations are provided in the end.
Besides editing, PEERenables you to write tests from the beginning using an empty sequence x₀.
Meta claims to have enhanced the quality and diversity of the plans, edits, and documents generated by PEER because of several mechanisms it has implemented.
For quality
PEER prepends control tokens for the output sequences and uses these tokens to guide the model’s generations. Here are some examples:
Instruction: this token controls whether the document begins with a noun, verb, etc.
Length as a proxy for the extent of details in explanations.
Word overlap to prevent overlapping words in the edit and explanation to ensure that the generated plans are not providing trivial edits by utilizing the specification inputs exactly.
Number of words to control the difference in the number of words between xₜ₊₁ and xₜ.
For diversity
To evaluate PEER’s ability to improve diversity, Meta has trained the model to perform edits on provided documents across multiple domains, especially the ones without edit histories. PEER has a collection of naturally occurring edits for texts obtained from Wikipedia, Wikinews, and the subforums of StackExchange.
Limitations
A significant drawback is that the model generated many false claims not backed by the documents. Generally, people rely on such results without explicit fact-checking. Since PEER represents edits by rewriting the entire paragraph, it is impossible to deal with lengthy documents in a time-efficient manner.
Moreover, the evaluation technique is limited as it only evaluates PEER and other similar models based on a small subset from only a few domains. The collaborative potential of PEER is also explored menially. Undertaking more extensive research on human-AI interactions would be challenging.
Nevertheless, the model is a significant step forward in improving collaborative writing. It can be actuated further to find more suitable ways to evaluate texts with human assistance and improve PEER’s efficiency in processing entire documents.
According to reports, Dubai’s Virtual Assets Regulatory Authority, or VARA, has granted provisional regulatory approval to Blockchain.com to operate in the region. The London-based cryptocurrency company, which serves as both a Blockchain wallet and a cryptocurrency exchange for users, is now the most recent in a line of digital asset companies expanding in the Gulf as the area strives to become a center for blockchain technology.
As economic rivalry in the Gulf area escalates, the United Arab Emirates (UAE) has been pushing for the creation of virtual asset regulations to draw in new business models.
Since the inception of a cryptocurrency regulator and corresponding legislation by Dubai’s prime minister and ruler Sheikh Mohammed bin Rashid Al Maktoum in March, VARA has given the clearance for companies including Crypto.com, OKX, and FTX subsidiaries to offer cryptocurrency-focused services in the nation. The creation of a new license program and rules for platforms that provide marketing and advertising services linked to cryptocurrencies were also announced by VARA. All virtual asset service providers must now adhere to the new regulations and disclose any advertising intentions behind their offerings in order for security precautions to safeguard customers.
In collaboration with colleagues from Bogazici University, researchers at Oxford University’s Department of Computer Science have created a novel artificial intelligence (AI) system that allows autonomous vehicles (AVs) to achieve more reliable and safer navigation capability, especially under adverse weather conditions.
Yasin Almalioglu, a part of the research team, said that AVs’ difficulty in achieving precise positioning during challenging adverse weather is a significant reason why these have been limited to relatively small-scale trials. For example, weather such as snow or rain may lead to an AV detecting itself in the wrong lane before a turn or stopping too late at an intersection because of imperfect positioning.
To overcome this issue, Almalioglu and his colleagues developed a new, self-supervised deep learning model for ego-motion estimation, which is a crucial component of an AV’s driving system. It estimates the car’s moving position relative to objects observed from the car itself.
The model brought together highly detailed information from visual sensors (which can be distorted by adverse conditions with data from weather-immune sources, so that the benefits of each of them can be used under various weather conditions.
The model was trained with the help of several publicly available AV datasets, which included data from multiple sensors such as radar, cameras, and lidar under diverse settings, including variable darkness/light and precipitation. These were used to generate algorithms to rebuild scene geometry and evaluate the car’s position from novel data.
The researchers proved that the model showed robust all-weather performance under various test situations, including conditions fog, rain or snow during both day and night. The team anticipates that this work will bring AVs one step closer to safe and smooth all-weather autonomous driving and, ultimately, a broader use within societies.
Starbucks, a well-known international coffee chain, has teamed up with blockchain service provider Polygon to create a brand-new non-fungible token (NFT) loyalty program that will debut later this year. This innovative Web3 experience, Starbucks Odyssey, combines the company’s popular Starbucks Rewards loyalty program with an NFT platform, enabling users to earn and buy digital assets that unlock premium experiences and rewards. Starbucks Odyssey aims to foster community among its most loyal customers by enabling them to earn a wider range of benefits.
According to a blog post by the company, Starbucks Odyssey is an extension of the current Starbucks Rewards model, where users earn “stars” that can be redeemed for perks like free beverages and Wi-Fi. Customers in the US can acquire digital collector stamps in NFT form that provide rewards and immersive experiences through the NFT loyalty program. Rewards could include virtual classes on making espresso martinis, invitations to special events at Starbucks Reserve Roasteries, and even vacations to the Starbucks Hacienda Alsacia coffee farm in Costa Rica.
Despite being housed on the Polygon blockchain, these NFTs will be purchased with a credit or debit card instead of a crypto wallet. Starbucks thinks that by decreasing the entry barrier, it will make it easier for customers to participate in the web3 experience. Additionally, it will give bundled pricing rather than adding extra costs to consumers’ transactions, such as “gas fees.”
Starbucks selected Polygon because of its ability to provide low-cost, high-speed transactions while running on top of the Ethereum network. By decreasing Polygon’s carbon footprint by 99.91% as a result of the Ethereum Merge, the scaling solution will be one step closer to achieving its goal of becoming carbon negative by the end of 2022.
Prior to the platform’s official debut later in 2022, Starbucks Odyssey’s waitlist started to take signups on Sept. 12.
Starbucks Rewards members can log in to the web app using their current reward program credentials in order to interact with the Starbucks Odyssey experience. Once in, users will be able to participate in a variety of activities, referred to by Starbucks as “journeys,” such as playing interactive games or completing tasks that will expand their understanding of the Starbucks brand or coffee in general. Members can accumulate digital collectibles in the form of NFTs as they accomplish these journeys. However, Starbucks Odyssey forgoes the technical jargon and refers to these NFT collections as “journey stamps.”
A selection of limited-edition-stamps NFTs will also be sold on the Starbucks Odyessy web app, which is compatible with mobile devices. Each journey stamp will have a point value depending on how rare it is, and the stamps may be purchased or transferred between users in the marketplace with ownership verified on a blockchain. As stamps are collected, members’ points will increase, giving them access to one-of-a-kind benefits and experiences.
Every stamp will include famous Starbucks artwork co-created with Starbucks partners as well as independent artists, allowing members and partners access to these prized assets for the first time. Additionally, a percentage of the profit generated through the sale of limited-edition stamps will be given to organizations important to Starbucks Rewards members and partners.
Since April, Starbucks has been exploring NFT collaborations in an effort to promote a novel convergence of blockchain and customer engagement. Watching how the Starbucks Odyssey performs by tapping into Starbucks’ coffee experience with the Web3 ecosystem will be fascinating.
