The global application of Artificial Intelligence (AI) in the real estate market is rapidly expanding, projected to reach $180.345 billion by 2030, with a compound annual growth rate of 35%. This market's rapid growth is driven by advancements in machine learning, predictive analytics, and the increasing demand for automation in property management. Key players in this market include Zillow Group, Compass, Redfin Corporation, and Reonomy, leveraging AI-powered tools to enhance customer experience.

Maxis Berhad, a Malaysian telecommunications company, and Huawei Technologies (Malaysia) Sdn Bhd have announced a strategic collaboration to enhance intelligent network operations through Artificial Intelligence (AI) and Machine Learning (ML). This collaboration aims to accelerate Maxis' digital transformation and improve user experience and operational efficiency via self-optimizing network technologies. According to Maxis, the collaboration will involve a comprehensive joint project focused on integrating AI and ML deeply into network management.

SiliconCloud's platform now officially supports batch inference for DeepSeek-R1 and V3 APIs. Users can submit requests via batch APIs to process large datasets within 24 hours, overcoming the limitations of real-time inference rates. A key highlight is the significant price reduction; DeepSeek-V3 batch inference is substantially cheaper than real-time inference.

Database engine developer MongoDB recently announced the acquisition of AI startup Voyage AI for $220 million. This acquisition aims to help businesses reduce the potential for 'hallucinations' in their AI applications, enhancing the reliability and accuracy of their products. Image note: Image generated by AI, image licensing service Midjourney. MongoDB President and CEO Dev Ittycheria stated in a press release...

Recently, the Meta AI team launched the video joint embedding prediction architecture (V-JEPA) model, an innovative initiative aimed at advancing machine intelligence. Humans can naturally process information from visual signals and recognize surrounding objects and motion patterns. An important goal of machine learning is to reveal the fundamental principles that drive unsupervised learning in humans. Researchers proposed a key hypothesis—the predictive feature principle—arguing that the representations of continuous sensory inputs should be able to predict each other. Early research methods utilized slow feature analysis.

Recently, Figure founder and CEO Brett Adcock announced a new machine learning model called Helix, aimed at enhancing the capabilities of humanoid robots in household environments. This news comes just two weeks after Figure announced the end of its collaboration with OpenAI, demonstrating their strong commitment to the field of robotics technology. Helix is a 'general-purpose' visual-language-action (VLA) model capable of processing visual data.

Google X's 'moonshot factory' has recently announced the independent development of a new startup, Heritable Agriculture. This new company aims to improve the way crops grow using data and machine learning technologies. Heritable Agriculture stated in a press release that plants are efficient and astonishing systems: 'Plants are solar-powered, carbon-negative self-assembling machines that rely on sunlight and water to thrive.' However, agriculture puts immense pressure on the Earth and its resources.

Recently, researchers at Keele University developed a new AI tool capable of identifying fake news with an accuracy of up to 99%, providing crucial support in combating online misinformation. The research team includes Dr. Uchenna Anie from the School of Computer Science and Mathematics, Dr. Sangeeta Sangeeta, and Dr. Patricia Aso-Ayobode. The team employed various machine learning techniques to design a model that scans news content and assesses its credibility. The researchers used an 'ensemble voting' technique, which...

OpenAI co-founder Ilya Sutskever recently stated that artificial intelligence researchers must find new ways to scale machine intelligence to overcome current limitations. Sutskever delivered a talk at the 2024 Neural Information Processing Systems (NeurIPS) conference in Vancouver, Canada, where he suggested that the era of AI pre-training is nearing its end and predicted the emergence of superintelligent AI. Sutskever believes that through better hardware, software, and machine...

The safety risks associated with lithium battery fires are often a cause for concern. To address this, scientists have proposed a method to provide early warnings of battery fires using sound. The study discovered that lithium-ion batteries undergo a series of chemical reactions before catching fire, leading to a gradual increase in internal pressure and ultimately causing the battery to swell. Due to the hard casing of the batteries, which cannot accommodate this swelling, the safety valve inside the battery bursts when the pressure becomes too high, creating a distinct sound.

AvePoint, a global leader in data management and governance solutions (NASDAQ: AVPT), announced today the official establishment of an AI lab with the support of the Singapore Economic Development Board (EDB). This strategic move will significantly advance innovative research in the fields of artificial intelligence and machine learning, further enhancing the AI capabilities of the AvePoint Confidence platform. The newly established AI lab will serve as a globally influential R&D center. Over the next three years, the lab plans to recruit more than

This week, MIT showcased a new model for training robots, aimed at addressing the challenges faced by imitation learning when introduced to small obstacles. Researchers pointed out that imitation learning can fail in conditions such as varying lighting, different environments, or new obstacles because robots simply do not have enough data to adapt. The team sought powerful data methods, like those used in models such as GPT-4, to tackle the problem. They introduced a new architecture called the Heterogeneous Pretrained Transformer (HPT), which aggregates information from different sensors and environments.

In the global wave of AI, India, a tech powerhouse, is experiencing significant market opportunities. According to a report jointly released by the IT industry association Nasscom and consulting firm BCG, the AI market in India is expected to reach $17 billion by 2027. Against this backdrop, the startup Neysa, led by seasoned tech entrepreneur Sharad Sanghi, emerged with the aim of capturing this growth opportunity by providing AI solutions to local and multinational companies. This Mumbai-based startup focuses on...

Recently, the U.S. Treasury announced that using artificial intelligence (AI) technology, they successfully recovered up to $4 billion in fraudulent and improper payments during the fiscal year 2024. This figure represents a significant increase from the previous fiscal year's $652.7 million, demonstrating the remarkable effectiveness of AI in combating financial fraud. Image source note: The image was generated by AI, with the image licensing provider being Midjourney. Treasury officials stated that they began quietly using machine learning technology to analyze vast amounts of data to identify and prevent fraud since the end of 2022.

Recently, Reserve Bank of India Governor Shri Shaktikanta Das issued a warning at a key meeting, stating that artificial intelligence (AI) and related platforms could exacerbate systemic risks in the Indian financial system. At this high-level meeting themed 'RBI90,' Das pointed out that while AI and machine learning open new business and profit growth opportunities for financial institutions, they also come with significant risks. He noted that a few AI service providers could dominate the market, leading to concentration.

In the world of artificial intelligence, the reasoning capabilities of machine learning models, particularly large language models (LLMs), have been a focal point for scientists. Recently, Apple's AI research team published a paper titled 'Understanding the Limitations of Large Language Models in Mathematical Reasoning,' shedding light on these models' limitations when addressing logical problems. In the paper, researchers demonstrate this through a simple mathematical question. They first posed a question about Oliver picking kiwis: as follows: Oliver picked 44 on Friday.

Recently, OpenAI announced that it is recruiting machine learning engineers for its newly established multi-agent research team. The news was shared by OpenAI's research scientist Noam Brown via social media. He stated, 'We believe that multi-agent systems are an important pathway to enhance AI reasoning capabilities, and previous experience in multi-agent systems is not a prerequisite.' Brown also encouraged professionals interested in researching this field to apply and join the team.