Start Your "Personalization Engines": New Book by David Edelman
Over the next five years, $2 trillion in revenue will shift to companies that understand how to create personalized experiences and personalized communications. Most companies aren't currently doing personalization very well, but new AI capabilities mean companies can personalize with unprecedented precision, and fine tune every customer interaction.
Those who compete using AI-empowered personalization will win today's war for customers, according to Boston Consulting Group (BCG) executives Mark Abraham and David Edelman in their new book, Personalized: Customer Strategy in the Age of AI (Harvard Business Review Press; ISBN: 1647826276). Predicated on a survey of 5,000 customers across ten countries, interviews with 100 senior industry leaders, and dozens of in-depth case studies the authors were involved in, the book is the definitive guide to harnessing AI to personalize the customer experience.
Read here: Morningstar
Five Functions where AI is already delivering Value
Key Findings:
Companies are ramping up spending on generative AI, especially in software development, customer support, and other areas.
AI is delivering real efficiency gains across functions, reducing customer support response times by a third and cutting some code-generation times in half.
More than most disruptions, AI requires some business redesign to capture value. Simply deploying the technology delivers little return on investment.
In sales and marketing, generative AI is deployed in generating dynamic, personalized content, personalized email marketing, social media engagement automation, automated account planning, and advanced training and support. By automating and optimizing these customer interactions, generative AI is boosting the productivity of sales reps and other marketing staff, shortening cycle times, reducing churns, and delivering better click-through rates through hyper-personalization.
One technology hardware company, for instance, is transforming content management by simplifying content creation, automating systems and workflows that synthesize, assemble, and publish content, and adopting generative AI tools for some roles. The company aims to reduce time spent on content by 30%. Pilots have already delivered promising results in a variety of uses, meeting and exceeding this goal.
Read here: Bain and Company
Will AI lead to superintelligence or just super-automation?
Engineers from Palo Alto to Beijing are racing to create superintelligence — an artificial intelligence (AI) that can think and reason, with an intellect far superior to our own. But existing state-of-the-art models may be on a path to offer “super-automation,” rather than superintelligence.1 These existing AIs are typically based on a transformer-based large language model (LLM) capable of natural language processing and understanding, and with the ability to generate content and carry out tasks. As companies pour billions of dollars into semiconductors to unlock ever-greater AI capabilities, it’s important to understand what superintelligence is, what might be needed to achieve it, and whether the latest generation of AIs will be an adequate foundation for these ambitions.
Read here: Goldman Sachs
The Illusion of AGI and the Dawn of Post-Cognitive Humanity
Key points
While AGI may outperform human cognitive functions, it might serve to reshape our engagement with reality.
As AI takes over cognitive tasks, our focus could shift toward creativity, intuition, and emotional depth.
The future lies in redefining ourselves, embracing human connections as essential aspects of existence.
As artificial intelligence grows more sophisticated by the day, the notion of Artificial General Intelligence (AGI) looms large—a machine that can think and reason like and even better than humans. But what if AGI, as we imagine it, is an illusion—contrived by our myopic expectations for super computation? What if it's true role is not to match or surpass human intelligence, but to fundamentally reshape how we engage with reality? This isn’t about machines becoming human; rather, it’s about machines taking over cognitive tasks and freeing us to explore a new, post-cognitive frontier.
Read here: Psychology Today
Adobe unveils AI video generator trained on licensed content
On Monday, Adobe announced Firefly Video Model, a new AI-powered text-to-video generation tool that can create novel videos from written prompts. It joins similar offerings from OpenAI, Runway, Google, and Meta in an increasingly crowded field. Unlike the competition, Adobe claims that Firefly Video Model is trained exclusively on licensed content, potentially sidestepping ethical and copyright issues that have plagued other generative AI tools.
Read here: Ars Technica