Google or Microsoft?
While?NVIDIA ?clearly is an undeniable frontrunner in the AI race, the competition between?Google and Microsoft? seems to be only intensifying – the verdict on who is truly better at AI remains to be seen. Will Microsoft’s commercial acumen trump Google’s model superiority?
A few days ago,?Vin Vashishta , founder of V Squared shared an?interesting thought ?where he said amid the intense competition between the two, the success of AI products hinges not just on technical capabilities, but also on effective product management.
He said that data and AI product managers are emerging as crucial players in this race, ensuring that monetisation, production, and commercialisation are prioritised from the get-go, instead of being an afterthought. “A competitor that is better at delivering solutions to customers will win even with less advanced capabilities and models,” he added, saying that?Google is better at AI ?than?Microsoft . But, the latter is strategising it better.
The approach to decision-making is quite unique for both.?Dipanjan Banik , a principal product manager at?Microsoft ?said that Google’s decisions tend to be more engineering-driven, with a focus on developing new technologies and capabilities that can be integrated into its products and services. “In contrast, Microsoft’s decisions are more product-driven, with a focus on delivering innovative products and services that meet the needs of its customers,” he added.?
That doesn’t mean that Google isn’t top of its league. The company?claims to be mindful ?of releasing its technology into the market. Previously, it has made significant contributions, including?Vertex AI ,?Google Maps ,?PaLM , etc.?
Amid the ongoing battle between Microsoft and Google,?NVIDIA ?is emerging as a clear winner — i.e. because nearly all the existing SOTA models are trained on NVIDIA GPUs, alongside providing infra support for cloud services.?
However, the ambitious Microsoft is looking to outplay the chip giant in its own game. The company is reportedly working on its own AI chips called ‘Athena’ that can be used to train LLMs and avoid costly reliance on NVIDIA, where it could possibly slash by a third.?Read:?Microsoft Joins the Chip-munks, Will Make its Own AI Chips.
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Blockchain and Crypto Advocate
1 年Depends on the time horizon. Post 2030 neither
Thank you for sharing, Mr. Gupta. Nice read. AI products require unique considerations, such as data quality, bias, and ethical concerns. Product managers must collaborate closely with cross-functional teams, including data scientists, engineers, designers, and legal experts, to ensure that AI products meet user needs, comply with regulations, and align with business goals. Effective product management also involves identifying and prioritizing the most valuable features, optimizing performance, and continuously monitoring and improving the product. By adopting a user-centric approach and leveraging best practices in product management, companies can maximize the potential of AI and deliver innovative and impactful products to market. Anubrain Technology is a developer working on AI, Computer Vision, NLP, IoT, software, web application & mobile app development. https://anubrain.com/. For a better understanding of the use of AI, read the page: https://anubrain.com/artificial-intelligence/.
ETL Dying?? No way - ETL and data preparation is the foundation for Data Analytics. GAI in ETL space is a myth as of now, long way to go for it. Hype around GAI is pretty evident in certain areas.
Sr. Analyst, Business Development at Globalbiz Outlook | Driving Growth with Content Marketing, Digital Strategies & Brand Enhancement | Empowering Industry Leaders & Innovators Globally
1 年Great Article, Loved Reading Thanks for sharing Bhasker Gupta!!