Investment Advice - Founders in the B2B and AI sectors should not anticipate securing funding easily [1] - Approximately 80% of potential investors may decline meetings with these founders [1] Market Reality - Securing funding in the B2B and AI space is challenging [1]

Infrastructure Importance - Countries benefit from having infrastructure within their borders [1] - Power plants, such as nuclear and water power plants, are considered beneficial infrastructure [1] Language Models as Infrastructure - Language models are viewed as similar to infrastructure [1]

Language Model Importance - Having a language model tailored to a specific country is crucial for building infrastructure for its people [1] - Using generic models built elsewhere may not adequately empower a country's economy due to a lack of cultural fluency [1] Localization Benefits - A language model that understands the local context, dialect, and culture is essential for empowering the people of a country [1]

I think us being Canadian is an asset. There's a lot of companies in Canada and around the world that are interested in working with non-American tech companies. You know, over the past few years, America has shown that they're willing to like turn off access to tech based on political reasons, right.We've seen connections between American tech and the American government is like less clear as time goes on. What does that mean. It means that Trump influences US tech companies.Seems to be. Yeah. It was like ...

I don't think Sam Alden has done a service to the world by talking about how close AGI is. I think he has made several predictions now that are wrong and that were obviously wrong at the time he made them. >> I think AI will probably lead to the end of the world.>> You know, he's made illusions to things. He did a world tour where he spoke to every major leader the world over to tell them, hey, this technology is going to poses an existential threat. And I think that was academically disingenuous and I thin ...

Company Focus & Strategy - Cohere is uniquely focused on bringing large language model (LLM) technology to enterprise, training models for enterprise tool use and API integration within businesses [1] - Cohere trains efficient models that can fit on two GPUs, aiming for a balance between performance, cost, and accessibility for enterprise deployment [1] - Cohere prioritizes Return on Investment (ROI) over Artificial General Intelligence (AGI), focusing on helping enterprises achieve practical AI deployments [14] Model Training & Data - While the transformer architecture remains largely unchanged, Cohere focuses on refining training methods, including the use of synthetic data to augment real-world data [1] - Data quality remains a bottleneck, requiring a combination of real-world and synthetic data, with in-house annotators creating real data [1] - Cohere releases model weights for non-commercial usage, aiming to build credibility within the research community while maintaining a commercial business model [10] Competition & Market - Cohere differentiates itself from consumer-focused companies like OpenAI and Anthropic by concentrating on enterprise solutions and knowledge worker augmentation [14] - The company views being Canadian as an asset, attracting companies interested in working with non-American tech companies due to geopolitical considerations [18] - Cohere believes that benchmarks are not always an accurate reflection of the utility value of models, as they can be gamified and may not align with enterprise use cases [4] Talent & Workforce - Cohere acknowledges the war for AI talent but emphasizes the importance of stability, purpose, and value alignment in attracting and retaining employees [5] - The company believes that LLMs will augment human work, automating boring tasks and allowing people to focus on creativity, communication, and strategic thinking [8] - Cohere foresees changes to the workforce similar to those brought about by previous technological revolutions, emphasizing the need for policies to ensure a smooth transition and address income inequality [8][9] Future Predictions - By 2026, Cohere predicts that users will be able to use language to interact with computers to automate tasks like filing expenses [21] - The company believes that the skill of prompting will become less relevant as language models are trained to better fit how people expect them to work [12] - Cohere anticipates that language will become a more important part of how people interact with computers, though graphic user interfaces will still be valuable [18]

The only thing that matters for culture is growth, like business growth. Because for a business that's growing at like an amazing clip, it's always going to have cultural sort of issues that, you know, make it kind of suck to like work there. But everybody's okay with that and leaned in because they see a path for themselves because what they're solving for will be more comp, more career progression, bigger scope, manage a team.they have a line of sight towards that. But then if you don't have enough growth ...

Hiring Challenges - Hiring managers often delegate excessively and lack clarity on their needs, leading to ineffective recruitment [1] - This lack of clarity hinders recruiters' ability to find suitable candidates [1] Best Practices - Active involvement from the hiring manager is crucial for making successful hires [2]

The three roles that I see that get fired over and over are CPO, CMO, and head of talent. They typically have 1 and a half to twoyear stints and then they like move on to their next thing, you know, sort of like quietly and discreetly. Most folks don't understand that they were fired, but when you're in the senior leadership team, you do.Why does that happen. I think it's very similar to the same deal of like any mishhire. It's muddy thinking.Like founders vaguely know what they want. ...

I always joke that Newton's law of motion applies to companies. Things in motion stay in motion. I can never remember anything going 1 million to 9 million and then flattening out to 12, let alone 1 billion to 9 billion.Just the trajectory alone, it implies 30 something the following year, which would be a significant slowdown. You'd have gone from a 9x year to a 3x year. I just don't know how to process. ...