After leaving Eternal, which he led for 18 years, one of India's most successful tech billionaires is making his first major bets on new projects.
Deepinder Goyal plans to introduce the Temple device, which is shaped like a bob, within six months. He stated that this wearable gadget, named after its placement location—the temple/temple area—is capable of tracking the body's metabolic state in real time.
According to Goyal, who gave an interview at his extensive farm in New Delhi, the device will be released as a wellness product backed by peer-reviewed research. The launch timeline could range from six months to a year.
Temple will be the first commercial product from his new venture since February, when he stepped down as CEO of Eternal Ltd., whose business verticals include food delivery, quick grocery delivery, and event ticketing.
Goyal explained that Temple is one of the experiments with risky ideas outside the Eternal group. His scientific project, which began as personal research to understand cerebral blood flow, led to the discovery of a new biomarker he termed 'entropy.' This indicator correlates with metabolic rate, providing deeper insights by measuring changes related to stress, meditation, recovery, sleep, and physical exercise. However, the scientific basis of this device has not yet been confirmed by independent scientists.
The Temple device will cost around $1000 and is primarily aimed at high-performers such as executives, athletes, and founders, rather than the mass consumer. Goyal emphasized that he is creating Temple primarily for himself, and the business is merely a side effect.
Despite Temple entering the already saturated wearable device market, including watches and rings that track heart rate, sleep, and fitness metrics, Goyal argued that these products use heart rate as a proxy for what is actually happening in the body, whereas Temple measures metabolic rate directly. He stated: 'Heart rate was supposed to be a substitute for metabolic rate. We found the real thing.'
In addition to Temple, Goyal also invested $20 million personally in LAT Aerospace. As reported by the Economic Times last March, this aviation enterprise aims to reduce congestion in India's largest cities by developing low-cost, short take-off and landing distance aircraft.
His vision is to create a network of eight-seater aircraft connecting small airfields, allowing passengers to bypass major airports and travel directly between cities, towns, and villages. Acknowledging the complexities of the project related to engineering, regulation, and infrastructure, Goyal noted that he has only a 0.1% expectation of success, but he believes such a network could promote economic activity beyond India's largest urban centers.
Goyal's long-term aspirations extend beyond both ventures. He expressed a desire for Eternal, formerly known as Zomato, to continuously transform rather than remain defined by its current business. He believes that Eternal's goal is to ensure the evolution of its DNA, because 'the moment you think you have reached the top, you are dead.'
Previously, Goyal co-founded Zomato under the name Foodiebay—a restaurant discovery platform that digitized menus and contained reviews. In 2010, it was renamed Zomato and subsequently expanded into food delivery. The company went public in 2021. A year later, Zomato acquired the online grocery store Grofers, which was renamed Blinkit and is now India's largest instant delivery firm. Last year, the group was renamed Eternal.
Gu Yushen, a Tsinghua graduate student who holds a special scholarship and has nearly 5000 citations, has joined DeepSeek in anticipation of the official release of DeepSeek V4, scheduled for mid-July.
DeepSeek is actively hiring specialists in algorithmic research, engineering, product development, operations, and data engineering in preparation for the launch of DeepSeek V4. Among the authors mentioned in the DeepSeek V4 scientific paper is Gu Yushen. He is a candidate of sciences from Tsinghua University and received the Tsinghua Graduate Special Scholarship for 2025, according to a report by Machine Intelligence.
Gu Yushen has officially joined DeepSeek, adding one of the most promising young AI researchers from Tsinghua to the company's staff. Previously, he received the Apple PhD Scholarship for 2025 and the Ant Group In-Tech Scholarship. He is a graduate of the PhD program in Computer Science at Tsinghua University, where he also completed his undergraduate studies. His research is conducted under the supervision of Professor Huang Minli in the Conversational AI group.
Gu's research focuses on improving efficiency throughout the entire lifecycle of large language models. His work covers pre-training, subsequent adaptation, and inference. He concentrates on three main areas: data selection for pre-training, where he develops theories and algorithms to optimize data selection for creating more capable and efficient models; model compression through knowledge distillation, where he designs methods for transferring knowledge from large models to smaller, more deployable ones; and developing efficient model architectures by exploring new structures that reduce computational costs while improving performance.
According to his Google Scholar profile, his total citation count reaches nearly 5000. Two of his works have exceeded the threshold of 1000 citations each: 'Pre-trained Models: Past, Present and Future' and 'MiniLLM: Knowledge Distillation of Large Language Models'. He has been the first author on several papers accepted at leading AI conferences such as NeurIPS, ICLR, ACL, and others.
Notably, Gu made a significant contribution to the series of hybrid architectural language models, Jet-Nemotron. This series demonstrates state-of-the-art accuracy with full attention while maintaining excellent efficiency. The 2-billion parameter version of Jet-Nemotron outperformed Qwen3, Qwen2.5, Gemma3, and Llama3.2 on MMLU and MMLU-Pro benchmarks, while achieving up to 53.6 times faster generation speed on an H100 GPU with a context length of 256K, surpassing larger full-attention MoE models, including DeepSeek-V3-Small and Moonlight.
As Gu himself noted, 'When hardware resources are limited, algorithmic innovations become the key to overcoming computational bottlenecks.' His research philosophy aligns with DeepSeek's emphasis on developing efficiency-oriented AI, making him a strategic acquisition for the team ahead of the V4 launch.
