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Let’s talk confidently about how to select the perfect LLM companion for your project. The AI landscape is buzzing with LargeLanguageModels (LLMs) like GPT-4, Llama2, and Gemini, each promising linguistic prowess. They excel at crafting captivating content, translating languages, and summarizing information.
How AI captures customer needs that human product managers miss Watch on YouTube TLDR In my recent conversation with Carmel Dibner from Applied Marketing Science, we explored how artificialintelligence is transforming Voice of the Customer (VOC) research for product teams.
The discussion explores practical applications of AI tools like ChatGPT and Claude in product development, including MVP refinement, customer testing, and marketing content creation. Mike brings valuable insights about the revolutionary transformation of product development through artificialintelligence.
GPT-3 can create human-like text on demand, and DALL-E, a machinelearningmodel that generates images from text prompts, has exploded in popularity on social media, answering the world’s most pressing questions such as, “what would Darth Vader look like ice fishing?” Today, we have an interesting topic to discuss.
Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage
In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.
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In this tenth and final episode in the Product Success Issues, we discuss the Uses of ArtificialIntelligence in Product Success Management. Specific uses in pulling together a product market strategy, mature processes, information for decision-making, understanding the customer and competencies are discussed.
More evidence this week of the impact of artificialintelligence (AI) on the tech job market as Workday revealed it is shedding 1,750 jobs – 8.5% of its workforce – because the company is restructuring and looking to AI for growth and efficiency gains.
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We're talking about a complete shake-up powered by automation and artificialintelligence (AI). In this eBook, see exactly how they're set to transform the way we approach sales and go-to-market (GTM) strategies. In this exploration, we're diving into predictions about the future of sales.
How AI captures customer needs that human product managers miss Watch on YouTube TLDR In my recent conversation with Carmel Dibner from Applied Marketing Science, we explored how artificialintelligence is transforming Voice of the Customer (VOC) research for product teams.
We’re talking about how artificialintelligence (AI) is changing the way we manage products and come up with new ideas. AI in the Product Development Lifecycle Discovery and Research Phase Largelanguagemodels can come up with ideas, but always keep humans in the loop.
Here’s our story how we’re developing a product using machinelearning and neural networks to boost translation and localization Artificialintelligence and its applications are one of the most sensational topics in the IT field. There are also a lot of misconceptions surrounding the term “artificialintelligence” itself.
Using a custom ChatGPT model combined with collaborative team workshops, product teams can rapidly move from initial customer insights to validated prototypes while incorporating strategic foresight and market analysis. By the time we launch, the market may have moved on from the problem we originally set out to solve.
That's why it is so important to be on top of the cutting edge solutions available in the market. ArtificialIntelligence has become a massive force that's to be reckoned with, as it's quickly transforming the landscape across multiple industries. Today, they come in the form of AI-based tools.
The core focus of these activities is on thorough market research, continuous customer engagement, and strategic product development. This led him to research and identify 19 core activities specific to product management, with clear separation from product marketing, sales, and go-to-market functions.
7:36] What part does artificialintelligence (AI) play in digital transformation? A lot of companies are pumping out demos of AI passing the bar exam or creating a marketing plan in 30 seconds. The marketing plan created in 30 seconds is not good enough to implement. The current wave of change is around generative AI.
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According to a Brookings Institution report , “Automation and ArtificialIntelligence: How machines are affecting people and places,” roughly 25 percent of U.S. Instead, Magnin suggests that product managers use machinelearning predictions as options they can provide to their users to choose from.
Speaker: Howard Dresner, Chief Research Officer, Dresner Advisory Services, LLC
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For our core business like cameras, plugs, and bulbs, we’re investing in internal innovation, especially artificialintelligence. We’re pushing the boundaries of computer vision and machinelearning. How do you make sure it’s representative of your market?
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(ArtificialIntelligence) AI and product management is a white-hot topic that runs the gamut, from the countless benefits to product managers all the way to replacing product managers…and everything in between. What is AI (ArtificialIntelligence)? Is MachineLearning the Same as ArtificialIntelligence?
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When did you first become aware of artificialintelligence (AI)? For those products that are in the market, not all of them have the architecture to support robust, data-driven decision-making. NLP allows you to enter text as if you’re speaking with a human and receive a reply from a computer in a similar style of language.
From an in-depth look into the product job market, to creating LLM workflows for product managers, read on for a quick recap on what popular articles were shared the most on Mind the Product in September. Everything wrong with the product management job market.
Artificialintelligence or “AI” is human intelligence possessed by a machine. It needs machinelearning and components of AI to work. AI-powered contact lenses Some of the artificialintelligence features are used to optimize the contact lenses. How does it work?
AI, predictive analytics, and machinelearning are helping apps feel more personal while taking some of the guesswork out of product decisions. In 2025, more companies are using artificialintelligence to improve product decisions and automate key parts of the user journey. Its also changing how teams build them.
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Gain insights into the AI revolution and discover how to leverage artificialintelligence for a competitive edge in today’s fast-paced corporate landscape. One such technology that has rapidly transformed industries and revolutionized business operations is ArtificialIntelligence (AI).
Known as the Martech 5000 — nicknamed after the 5,000 companies that were competing in the global marketing technology space in 2017, it’s said to be the most frequently shared slide of all time. – lie beyond the realms of this article but one thing is clear: this market is HUGE. What is a marketing technology stack?
All disruptive technologies start selling first to small companies, the early adopters in a market. Then, as the customer base and market matures, successful disruptive technologies evolve with them, adding the sophistication that ever larger customers need as they scale. I studied artificialintelligence in college in 2004.
The outbreak of the covid-19 pandemic has damaged market landscapes. There is a rare aspect within a market landscape that hasn’t been touched by any technologies. Most importantly, big data and machinelearning have paved the way for robotics automation and various software applications. increase in the market share.
The market doesnt need another AI gimmick. The obsession with appearances has two big downsides: Buzzword, without strategy: Instead of focusing on how AI can actually enhance their business, startups are treating it like a marketing gimmick. Stop trying to look like an AI startup and start to be one instead. Saving time andmoney.)
In others, though, it’s clear they’re more of a response to market demand than a well-thought-out solution. Allow me to make the case that to do this effectively, you need to fully grasp the “superpowers” of largelanguagemodels (LLMs). The real difference lies in whether these features address genuine user needs.
We found that artificialintelligence is starting to help companies make better product management decisions. 26:23] You’ve commented before on the single most important question product managers can ask to determine whether they have nailed product market fit. What is that question?
Before OpenAI, Karina was at Anthropic, where she led post-training and evaluation work for Claude 3 models, created a document upload feature with 100,000 context windows, and contributed to numerous other innovations. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.
Takeaway: Functional departments, such as customer service, sales, and marketing, should work together to provide customers with a world-class, cohesive, personalized experience across the customer journey. C-level leaders set the tone for the entire company and showcase the importance of building strong customer relationships.”
Suddenly it seemed that generative AI might transform industries from education to marketing. The trickiest thing about largelanguagemodels (LLMs) is that they’re great at appearing plausible, even when they’re wrong. . Specifically, the latest LLMmodels “hallucinate,” meaning they just make things up.
Yet, PwC reports that 60% of organizations have experienced security incidents related to AI or machinelearning. Keeping up with changing security threats The vast amounts of data required to train AI models create new attack surfaces for cybercriminals to exploit.
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