Tesla is negotiating a partnership with Intel to produce its upcoming AI5 chip, significantly reducing manufacturing costs. The deal aims to lower expenses to approximately 10% of those for Nvidia’s equivalent chip while also decreasing power consumption by one-third. Although a formal agreement has not yet been reached, the potential collaboration could have a substantial impact on the AI hardware market.
At a recent shareholder meeting, Tesla CEO Elon Musk revealed the company’s ambitions to innovate in the AI sector through this chip-manufacturing partnership. The development comes amidst a growing demand for efficient AI technologies, as companies seek to balance performance with cost-effectiveness. If successful, this initiative could set a new standard in the industry, allowing for broader adoption of AI solutions across various sectors.
In other news, Bengaluru-based digital lender Finnable has successfully raised Rs. 250 crore in a funding round led by Z47, formerly known as Matrix Partners, and TVS Capital. This latest investment brings Finnable’s total funding to Rs. 540 crore. The company intends to use these funds to enhance its technology infrastructure, expand its branch network, and introduce new financial products, including loans against property. By June 2025, Finnable’s assets under management are projected to reach Rs. 2,924 crore, highlighting its rapid growth in India’s fintech landscape.
The Indian banking, financial services, and insurance sector is expected to create around 250,000 new jobs by 2030, particularly in tier-2 and tier-3 cities. Candidates will generally need a bachelor’s degree, along with strong digital literacy, customer service skills, and effective communication abilities. Aspiring job seekers are encouraged to engage with recruitment portals, pursue short courses in finance and risk management, and develop their soft skills to enhance their employability in this dynamic sector.
Additionally, recent literature has emerged focusing on how large language models function, their real-life applications, and best practices for building with them. These resources cater to both beginners and advanced readers, covering topics such as theory, coding tools, business applications, and ethical considerations. Such materials bridge the knowledge gap for those interested in working with AI and language-based technologies.
In the cryptocurrency market, traditional holders of major coins like Bitcoin are increasingly diversifying their investments into lesser-known tokens. This shift is primarily driven by a sluggish market for established cryptocurrencies, leading digital asset treasury firms to seek higher returns. Analysts caution that this move toward more exotic and less liquid tokens may introduce greater market volatility and increased risks for investors.
