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From April 25 to 26 local time, the AI & Big Data Expo Global 2019 was held in OlympiaLondon. This is a two-day expo showcasing the next generation of technologies and strategies in AI and big data, attracting more than 4,000 relevant practitioners. Dr. Wei Cui, co-founder and chief scientist of Squirrel AI Learning, was invited to give a speech at the Expo and he also shared his insights into AI with senior executives from Darktrace, a UK cyber security company; SAP, the world’s third largest independent software providerReddit, one of the largest social platforms in the United States; and Just-Eat, a Danish company equivalent to “Meituan”.

The themes of this expo include: enterprise AI, AI and Internet of Things data analysis, big data business solutions and AI technology solutions.

Dr. Wei Cui from Squirrel AI Learning: How Does AI Provide Economical and Individualized Education for Every Family in China

Dr Wei Cui, chief scientist of Squirrel AI Learning, introduced the AI adaptive learning system independently developed by Squirrel AI Learning. This system can continuously monitor and evaluate students’ individual abilities, find their weaknesses in learning and allow students to progress at their own pace so as to improve their learning. The system provides optimized learning solutions and simultaneous counseling to maximize learning efficiency and improve students’ ability to acquire knowledge and skills.

For years, the lack of senior teachers and geographical problems have adversely affected the popularization of quality education in China. Squirrel AI hopes to train “super teachers” through AI and provide one-on-one tailored education for students.

In his speech, Dr. Wei Cui introduced the basic technologies used to build the system and carry out performance evaluation experiments. Squirrel AI Learning’s adaptive educational engine includes three layers of architecture: ontology layer, algorithm layer and interactive system. Content-focused, the ontology layer incorporates learning maps and knowledge maps. Squirrel AI Learning independently developed the technology to disassemble knowledge points at a super-nano level, making for more accurate determination of the knowledge points students are supposed to master. Take mathematics of junior high school as an example. Squirrel AI Learning can disassemble the 300 knowledge points into 30,000.

The algorithm layer includes content recommendation engine, students’ user portrait engine and target management engine. Based on user status evaluation engine and knowledge recommendation engine, Squirrel AI Learning will build a data model to detect the gaps of knowledge for each student accurately and efficiently and then recommend corresponding learning content according to these gaps.

The interactive system collects interactive data to learn more about students and improve the algorithm. Squirrel AI Learning cooperated with Stanford Research Institute to study the machine-student interactive system. Its self-developed MIBA student behavior data acquisition system won big award at the World Conference on AI.

In addition, the MCM system developed by Squirrel AI Learning can disassemble students’ model of thinking, capabilities and methods of learning and then provide training of these abilities and methods in a single subject according to students’ learning status.

By the beginning of this year, Squirrel AI Learning has set up nearly 2,000 learning centers in more than 300 cities across China with nearly 2 million registered student users. Last year, Squirrel AI donated 1 million free study accounts to underprivileged families to promote education fairness.

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Marc Teerlink, SAP’s Global Vice President: How to Realize “Gold Rush” in the Era of AI

Marc Teerlink, SAP’s global vice president, talked about how enterprises adapt to the era of AI. The world is currently on the verge of a “gold rush” with AI. Teerlink’s speech is about how AI and machine learning bring wealth to enterprises as well as experience sharing by current industry leaders.

SAP estimates that by 2030, more than 60% of jobs will face great changes. About 51% of work will be automated but only 5% will be completely done by machine. Therefore, Teerlink prefers to call this era the era of “augmented intelligence” in which technology is used to enhance human’s ability to process information.

Teerlink said that partners using SAP machine learning software have translated algorithms into commercial profits. He cited one example: VALE, a Brazilian-based global mining company, used machine learning to optimize its procurement application process.

The current process is a purely manual one in which scattered information is distributed in multiple files and systems. As a result, 25-40% of the purchase requisitions are rejected every month due to errors, resulting in severe rework.

In the past few years, VALE has started to use SAP Leonardo open innovation framework based on design thinking and technology to define a re-conceived application process that provides an SAP Fiori application accessible from any device to help users complete the end-to-end process without logging into any back-end device systems.

Machine learning for image recognition is the core of this process. Image recognition algorithm is integrated into the application of SAP Leonardo machine learning so that maintenance technicians can recognize the serial number of the materials of any parts that need to be replaced by taking pictures of them. Even without Internet access, technicians can still take pictures of the parts and complete the purchase application process later.

Once the parts are identified, the application will connect to the back-end system and find the correct procurement process for the material, be it contract process or purchase requisition, and then the application will automatically complete the procurement requisition process and check whether the parts have been requested on the previous shift or exist in any nearby deposits.

This procedure streamlines the procurement application process, reduces the delivery cycle of procurement, reduces spare parts inventory, thus reducing working capital and improving labor efficiency.

Enterprises like VALE that have long engaged in AI have already tasted the sweetness. SAP observes that these enterprises generally have the following characteristics: the strategic center of C-level executives, increased competitive differentiation, new income and profitability, and strategies covering the whole field. They all view data as important assets.

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Dave Palmer, Technical Director of Darktrace: How Does AI Affect Cybercrime

Darktrace is a British start-up in network security that mainly provides “corporate immune system” that can be deployed in company network to monitor network anomalies. Once suspicious behavior occurs within the network, Darktrace will remind IT managers and, when necessary, automatically trigger protection behavior to mitigate network attacks. Unlike traditional methods that rely on rules or signatures, this automated technology enables security teams to focus on high-value tasks and even to counter fast-moving automated attackers.

Dave Palmer believes that AI will greatly increase the impact of cyber crime on enterprises. Due to the open source environment of computer science and the introduction of various API & SDK by large companies, even people without relevant backgrounds can easily acquire and use AI technology such as face recognition and voice recognition, which greatly lowers the threshold of cyber crime.

Unlike planting a virus or malicious software in the system in the past, network attacks now take many forms and are more and more extensive. For example, stealing your data for blackmail, monitoring important meetings of competing companies, or modifying your data from the bottom to influence the decision-making of your superiors, etc.

Therefore, many companies are deeply engaged in network security protection. For example, Microsoft launched its cloud-based risk security detection tool in 2017 with which developers find bugs and other security vulnerabilities in software to be released or used. The tool is designed to fix bugs before software vulnerabilities occur.

Anand Mariappan, Senior Director of Reddit: Development History of Reddit Machine Learning

Anand Mariappan, senior director of Reddit in charge of search and machine learning engineering, reviewed the history, current projects and future direction of Reddit’s machine learning that covers data platforms, feed rankings, recommendations, user and channel similarities.

Reddit, the US version of “Tianya” and “Baidu Tieba”. According to the data released by Alexa, Reddit is the fifth largest website in the United States, ranking 14th in the world and even surpassing Facebook in traffic. Reddit currently has 330 million active users, nearly 140,000 active communities, 12 million posts and nearly 100 million comments per month. In February this year, Tencent invested $150 million into Reddit. Reddit is currently valued at $3 billion.

Reddit has been building and improving data pipelines over the past few years. Since 2014, it has been using Amazon S3 and Hive to gradually build a multilevel database architecture based on MIDAS, and now the architecture is based on Google’s BigQuery.

Reddit has 140,000 sub-Reddit, which can also be understood as channels. Recommending relevant channels to users is an important way to increase user participation, which was done through manual selection. Now deep learning takes the place of manual selection. Through deep learning, Reddie can directly gather all comments in a channel into a file and then use the end-to-end doc2vec model to train and get semantic information to assist in the matching.

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Reddit also optimized the recommendation on the home page. It uses large-scale logistic regression algorithm to make personalized content recommendation based on parameters such as time, channel, user interest, and device.

Mariappan said Reddit is currently developing machine learning programs to optimize personalized models, and has achieved amazing results in the early development phase by using models on TensorFlow to improve the quality of content recommendation.

Ben DiasHead of Royal Mail: From Zero to Data Science

Ben Dias, head of analysis and data science at Royal Mail, shared his experience of “from zero to data science” and summarized seven key points, hoping to help enterprises accelerate their progress in developing data science by providing practical skills, tools and technologies.

First, be prepared. Enterprises should first understand themselves and be fully prepared in areas of data processing, standard business intelligence analysis, underlying architecture and technology stack.

Second, lay more emphasis on retention of talents than recruitment. Don’t rush to look for talents outside the enterprise. Instead, enterprises should train and retain talents and nurture suitable office culture.

Third, don’t hire “super chicken”. Super chicken refers to highly talented and motivated employees. Margaret Heffernan, an expert in business management consulting, pointed out in a TedTalk that a team of geniuses will not be more efficient, but rather has disastrous performance. Successful teams do not need superstars but collaborative staff working based on consensus.

Fourth: Don’t put all eggs in one basket. Enterprises should comprehensively consider short-term benefits, medium-term considerations and long-term planning.

Fifth, adopt the model of Lean StartupLean Startup is a method of developing business and products, aiming to shorten product development cycle and quickly find out whether the proposed business model is feasible. This model is achieved through a combination of business hypothesis-driven experiments, iterative product release and proven learning.

Sixth & Seventh: You must change everyone and everything & apply scientific methods to everything.

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Gilles Comau, Head of Just Eat AI: Challenges and Opportunities of Building Personalized Strategies.

Gilles Comau is Just Eat’s director of machine learning and AI. Just Eat, founded in 2001, is a take-out ordering website in Denmark. It provides applications to enable consumers to easily place orders and make payment. Now it has operations in many countries around the world. In 2014, Just Eat was successfully listed on the London Stock Exchange with a market value of $2.4 billion.

Comau’s speech is centered on the challenges and opportunities of building personalized strategies. Delivery services involves millions of similar but greatly different products. Delivery areas also have geographical limitations, which needs to be optimized through algorithms.

Just Eat’s big data analysis helps predict what kind of food users will order at a particular time. For example, big data generated by Just Eat enables analysts to predict which regions are most likely to order healthy food and which regions prefer food collection to delivery.

Results of big data analysis of users’ eating patterns and trends will be provided to restaurants to help them meet various needs and increase menu items. This can help them grow their business.

Just Eat has more than 60 million accounts and at least 7.5 million people have multiple accounts. Therefore, Just Eat needs to use data science to delete repeated accounts and link users with similar attributes.

The match between restaurants and users helps users find delicious food more conveniently. The restaurant’s attributes are mainly based on the food it mainly recommends, including the flavor, attributes, taste, and ingredients of food. User profile is determined by ordering habits, preferences, social attributes, trading habits, contact information, etc.

These attributes will help Just Eat build a two-dimensional and visual vector search space. When searching delicious food through key words, users can get what they want just by judging which vector their key words are the closest to.

Machine learning is also used to deliver orders to customers fast through prediction of driver paths and improvement of communication efficiency so as to deliver food fast, maintain correct delivery order and prevent lost delivery orders.

SOURCE Squirrel AI Learning

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Declaration on longevity and precision medicine launched at Abu Dhabi Global Health Week

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  • Establishing actionable frameworks to advance precision medicine and longevity science
  • The declaration highlights the impact longevity and precision medicine can have on supporting healthy communities, and engages leaders to work towards actionable solutions, drive consensus among global peers, and invest in long-term solutions
  • It brings together leading healthcare and academic institutions to redefine and improve health outcomes while aligning on key global healthcare priorities

ABU DHABI, UAE, April 18, 2025 /PRNewswire/ — A groundbreaking ‘Declaration on Longevity and Precision Medicine’ was launched at Abu Dhabi Global Health Week (ADGHW), marking a historic milestone in the quest to transform healthcare delivery and research worldwide.

As the first initiative of its kind, and developed in collaboration with leading international health organisations, academic institutions, and industry pioneers, the declaration establishes key principles to accelerate the advancement of precision medicine and longevity science.

Speaking at the launch, H.E. Mansoor Ibrahim Al Mansoori, Chairman of the Department of Health – Abu Dhabi (DoH) stated: “Healthy populations lead to healthy communities, stronger social cohesion, and fuels economic growth. This declaration unites global leaders to harness emerging technologies responsibly and deliver the benefits of precision medicine to all. Because health knows no boundaries, we are working together towards actionable and long-term solutions.”

Developed in collaboration with experts worldwide, the declaration aims to drive the adoption of personalised care and promote research into extending healthy lifespans. It highlights the urgency of addressing the widening healthspan-lifespan gap, which currently stands at nearly a decade globally.  

The declaration comes at a critical time as the World Health Organization projects the global population aged 60 and older will double to 2.1 billion by 2050. Concurrently, the precision medicine market is expected to grow from $81 billion in 2023 to over $175 billion by 2030.

The United Arab Emirates (UAE) is rapidly emerging as a regional and global leader in the longevity market, driven by pioneering regulatory frameworks, investments in precision medicine, and groundbreaking initiatives such as the world’s first licensed Healthy Longevity Medicine Centre.  From $19 billion in 2020, the UAE’s longevity market is estimated to reach $32 billion by 2026.

The declaration outlines bold commitments to advance longevity science, artificial intelligence (AI), driven diagnostics, and personalised therapeutics. It sets forth six key pillars: advancing research and innovation, enhancing collaboration and knowledge-sharing, investing in education and workforce development, advocating for supportive policy and regulation, upholding ethics and responsible practices and engaging the public about longevity research and its implications for health and society.

Signatories who convened at ADGHW to formalise their commitment which was led by DoH included, M42, Masdar City, PureHealth, Illumina, NYU Abu Dhabi, University of Pennsylvania, Aldar, Children’s National Hospital, Burjeel, Children Hospital of Philadelphia, and the Institute for Healthier Living Abu Dhabi (IHLAD).

PwC Middle East, a strategic partner in the initiative, highlighted the global significance of this declaration in advancing global healthcare priorities.  Lina Shadid, Health Industries Leader, PwC Middle East stated: “The declaration on longevity and precision medicine provides a global blueprint for integrating AI, genomics, and precision healthcare into mainstream medical practice and within the health ecosystem, to accelerate the adoption of life-changing medical innovations worldwide.

The declaration reflects Abu Dhabi’s ongoing commitment to shaping the future of health through knowledge-sharing, investment in research, and the integration of emerging technologies. By convening global experts and institutions, DoH is ushering a new era of precision medicine —one that prioritises personalised and preventative care, and enhances quality of life for populations worldwide.

Governments, health organisations and relevant stakeholders worldwide are encouraged to sign this declaration. For more information, please visit: https://www.adghw.com/

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ADGHW is a major government initiative from DoH and serves as a platform for innovation and collaboration under the theme ‘Towards Longevity: Redefining Health and Well-being.’ It places a strong emphasis on community-driven health and well-being, with a proactive approach centred around preventive, personalised, and holistic care. 

For media inquiries or interview opportunities, please contact:  
Maroun Farah, Senior Media Relations Manager, Weber Shandwick
E: [email protected] 
T: +971 55 166 2557

For media inquiries, please contact: Mariam Al Marzooqi 
[email protected]
+971 50 536 6660 

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Yarbo Secures $27M+ Series B Funding to Accelerate Global Growth, Innovation, and Ecosystem Expansion

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NEW YORK, April 18, 2025 /PRNewswire/ — Yarbo, the world’s first year-round multipurpose intelligent yard robot, has successfully closed its Series B funding round, raising approximately $27M USD. The round was backed by a group of strategic and financial investors, bolstering Yarbo’s vision of reimagining how the world handles outdoor work – one season at a time.

This fresh injection of capital will turbocharge Yarbo’s ability to scale mass production, enhance supply chain resilience, and deepen investment in R&D, fuelling faster product optimisation and iteration. The company also plans to accelerate talent acquisition, strengthen liquidity, and push forward with pre-IPO planning as it sets its sights on global expansion and long-term market leadership.

A Decade of Innovation, One Yard at a Time

Founded in 2015, Yarbo began life as Snowbot: targeting the infamously tough task of snow removal, a long-standing pain point for homeowners. Since then, the company has transformed from a niche robotics brand into a global category leader in outdoor automation, now operating under the Yarbo name.

With its signature “1+N” modular design, Yarbo offers year-round functionality powered by one intelligent core robot and a growing family of interchangeable modules. From snow blowing in winter, to lawn mowing in summer, to leaf blowing in autumn, Yarbo has become a household name for those who’d rather relax in their gardens than maintain them.

In 2022, Yarbo’s crowdfunding campaign raised over $3.45M USD, and by 2024, its own direct-to-consumer full-payment pre-order campaign generated 6,000+ orders. With momentum continuing to build, Yarbo expects 4–5x sales growth in 2025, supported by expansion across North America, Europe, Japan, and Australia.

New Trimmer Module Nears Mass Production

Hot off the back of a successful Spring Sale & Robotic Trimmer Launch livestream in early April – where Yarbo moved 702 total units, including 284 trimmers, and raked in over $850,000 in sales within 2 hours – the new Trimmer Module is fast approaching mass production.

Designed to tackle edges, tight spots, and other areas your mower can’t reach, the Trimmer expands Yarbo’s spring and summer capabilities, perfectly complementing the Lawn Mower and Blower modules.

Yarbo’s modular expansion doesn’t stop there. Future modules are in development to cover tasks such as granular or liquid spraying, moving your garbage bins to the curb, dog waste picking, and even fruit harvesting. All without changing the core robot. The goal? A full-spectrum, “1+N” yard ecosystem that meets every seasonal demand and makes yard work a relic of the past.

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The Future of Yard Work Is Modular

After a well-received showcase at CES 2025, Yarbo continues to build on its latest product innovations, including:

  • “Follow Me” Mode – Let Yarbo visually track and follow you, hands-free.
  • 3,500 lbs pulling capacity – Yes, really. From firewood to garden carts.
  • Quick-swap design – Change tracks, antennas or modules in under 5 minutes.
  • Halow-powered Data Center – Better connectivity, stronger signal, wider coverage.

Whether it’s clearing leaves, trimming lawn edges, or prepping for a summer BBQ, Yarbo is the robotic outdoor companion for every season. The future looks even brighter (and a lot less back-breaking) for yard owners everywhere.

Interested in trying Yarbo for yourself? We’re happy to arrange media test units, product demos, and interviews to showcase just how easy spring yard work can be. Yarbo is actively recruiting distributors in both North America and Europe. For those interested, please email [email protected] or visit www.yarbo.com/become-a-dealer.

For more information on Yarbo, please visit www.yarbo.com.

About Yarbo

Yarbo is the world’s first multi-purpose yard robot, designed to meet over 20 kinds of yard care demands such as snow blowing, lawn mowing, leaf blowing and more. The fully autonomous robot’s core features include all-season yard maintenance, a modular design, data connectivity capabilities, wireless charging, smart route planning, app control and remote control and next-generation smart obstacle avoidance with patented precise positioning and navigation technology. This together provides yard enthusiasts with versatile and easy-to-use options for a stress-free, hands-free yard care experience. Established in 2015, Yarbo’s mission is to create value and make a difference in people’s lives through being the world’s leading intelligent outdoor equipment provider.

For inquiries, please contact:

Kathy Zhang
[email protected]

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Bybit launches Crypto Surf: Copy Traders and Bots Battle for 250K USDT

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DUBAI, UAE, April 18, 2025 /PRNewswire/ — Bybit, the world’s second-largest cryptocurrency exchange by trading volume, is making waves with its latest trading showdown: Crypto Surf: Ride the Waves with Trailing Stops. This high-octane competition invites traders to rally behind either copy trading or trading bots, battling it out for their share of a prize pool worth up to $250,000 in USDT.

Running from April 18 to May 19, 2025, at 12 a.m. UTC, the event introduces a squad-based structure where users choose their camp, trade strategically, and compete across PnL, ROI and trading volume leaderboards. With a dynamic reward structure, participants can also win by predicting which squad will come out on top.

Prize Pool Distribution Highlights:

  • 40% to the champion squad
  • 30% to the runner-up 
  • 25% to the top 100 individual traders by volume
  • 5% to users who correctly predict the winning squad

The event brings together the best of both worlds: the strategic finesse of copy trading and the automated power of trading bots. It celebrates innovation, user choice, and the thrill of crypto trading.

Participants must hold a minimum wallet balance of $1,000 in USDT, generate at least $10,000 in squad volume, and complete identity verification Level 1 to qualify. Users can only register for one squad and vote once to predict the winner. Rewards will be distributed within 14 business days of the event’s completion.

The total prize pool will scale in line with event volume milestones, starting at $1.2 billion and unlocking up to $2 billion in traded volume for the full $250,000 in USDT.

Bybit continues to redefine the competitive trading landscape – bringing fun, strategy and serious rewards to its global community.

#Bybit / #TheCryptoArk

About Bybit

Bybit is the world’s second-largest cryptocurrency exchange by trading volume, serving a global community of over 60 million users. Founded in 2018, Bybit is redefining openness in the decentralized world by creating a simpler, open, and equal ecosystem for everyone. With a strong focus on Web3, Bybit partners strategically with leading blockchain protocols to provide robust infrastructure and drive on-chain innovation. Renowned for its secure custody, diverse marketplaces, intuitive user experience, and advanced blockchain tools, Bybit bridges the gap between TradFi and DeFi, empowering builders, creators, and enthusiasts to unlock the full potential of Web3. Discover the future of decentralized finance at Bybit.com.

For more details about Bybit, please visit Bybit Press
For media inquiries, please contact: [email protected]
For updates, please follow: Bybit’s Communities and Social Media

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