Posts

Showing posts with the label GenerativeAI

How to win with AI: Insights from a CEO

Image
The rising pressure to use AI AI is no longer a future concept. It’s on the table in every leadership meeting I’m part of, and it’s becoming a top-down priority across industries. More CEOs, including myself, are asking their teams to integrate AI into their workflows. The expectation is clear: every team should be using AI to improve efficiency and performance. The pressure to operate with an AI-first mentality is real, but many teams are struggling to understand what that actually means in practice. The goals (faster output, lower costs, better quality) are valid. But when teams jump in without the right strategy, the results can miss the mark. I’ve seen companies spend heavily, lose time chasing fixes, or end up with translations that need so much cleanup, it would have been faster to use conventional human or machine translation. So let’s reset the conversation. Being AI-first doesn’t mean using every tool you can find or building bespoke AI applications. It means knowing when and ...

Opportunity or Commodity? Investors Discuss The Language AI Thesis at SlatorCon

Image
Two seasoned venture capital investors, Shesh Amathnadu and Pramod Gosavi, joined the Investor Panel at SlatorCon Silicon Valley in early September. The pair shared their view on the language AI thesis and areas of opportunity within language AI with a 200-strong audience.  Amathnadu is Senior Investment Director at SK Telecom Ventures, the corporate venture arm of South Korea’s largest telecom operator SK, whose investments include Anthropic, Perplexity, and 12 Labs. Gosavi is Senior Principal at Blumberg Capital, a US-based B2B generalist investor, which makes investments from Pre-Seed to Series B from its two funds. With solid engineering backgrounds and more than a decade of investment experience, both Amathnadu and Gosavi have become experts in AI investing. Amathnadu discussed the current AI cycle and described the launch of ChatGPT in 2022 as an inflection point, which created a “clear differentiation of traditional machine learning [ML] versus generative AI.” In summary of ...