Brian Solis's Blog, page 12

AInsights: Exploring OpenAI’s new Flagship Generative AI Model GPT-4o and What It Means to You

OpenAI CTO Mira Murati Credit: OpenAI

AInsights: Your executive-level insights on the latest in generative AI…

OpenAI introduced GPT-4o, its new flagship, real-time generative AI model. The “o” stands for “omni,” which refers to the model’s ability to process multimodal prompts including text, voice, and video.

During its live virtual event, OpenAI CTO Mira Murati explained this version’s significance, “…this is incredibly important, because we’re looking at the future of interaction between ourselves and machines.”

Let’s dive-in to the announcement to explore the new features and what it means to you and me…

Increased Context Window

GPT-4o has a massive 128,000 token context window, equivalent to around 300 pages of text. This allows it to process and comprehend much larger volumes of information compared to previous models, making it invaluable for tasks like analyzing lengthy documents, reports, or datasets.

Multimodal Capabilities

One of the most notable additions is GPT-4o’s multimodal capabilities, allowing it to understand and generate content across different modalities:

Vision: GPT-4o can analyze images, videos, and visual data, opening up applications in areas like computer vision, image captioning, and video understanding.

Text-to-Speech: It can generate human-like speech from text inputs, enabling voice interfaces and audio content creation.

Image Generation: Through integration with DALL-E 3, GPT-4o can create, edit, and manipulate images based on text prompts.

These multimodal skills make GPT-4o highly versatile and suitable for a wide range of multimedia applications.

Humanity

Perhaps most importantly, CPT-4o features several advancements that make it a more empathetic and emotionally intelligent chatbot. In emotionally-rich scenarios such as healthcare, mental health, and even HR and customer service applications, sympathy, empathy, communications, and other human skills are vital. To date, chatbots have been at best, transactional, and at worst, irrelevant and robotic.

ChatGPT, introduces several key advancements that make it a more empathetic and emotionally intelligent chatbot.

Emotional Tone Detection: GPT-4o can detect emotional cues and the mood of the user from text, audio, and visual inputs like facial expressions. This allows it to tailor its responses in a more appropriate and empathetic manner.

Simulated Emotional Reactions: The model can output simulated emotional reactions through its text and voice responses. For example, it can convey tones of affection, concern, or enthusiasm to better connect with the user’s emotional state.

Human-like Cadence and Tone: GPT-4o is designed to mimic natural human cadences and conversational styles in its verbal responses. This makes the interactions feel more natural, personal, and emotionally resonant.

Multilingual Support: Enhanced multilingual capabilities enable GPT-4o to understand and respond to users in multiple languages, facilitating more empathetic communication across cultural and linguistic barriers.

By incorporating these emotional intelligence features, GPT-4o can provide more personalized, empathetic, and human-like interactions. Studies show that users are more likely to trust and cooperate with chatbots that exhibit emotional intelligence and human-like behavior. As a result, GPT-4o has the potential to foster stronger emotional connections and more satisfying user experiences in various applications.

Improved Knowledge

GPT-4o has been trained on data up to April 2023, providing it with more up-to-date knowledge compared to previous models. This is important for tasks that require more current information, such as news analysis, market research, industry trends, or monitoring rapidly evolving situations.

Cost Reduction

OpenAI has significantly reduced the pricing for GPT-4o, making it more affordable for developers and enterprises to integrate into their applications and workflows. Input tokens are now one-third the previous price, while output tokens are half the cost. Input tokens refer to the individual units of text that are fed into a machine learning model for processing. In the context of language models like GPT-4, tokens can be words, characters, or subwords, depending on the tokenization method used.

Faster Performance

Optimizations have been made to GPT-4o, resulting in faster, near real-time response times compared to its predecessor. This improved speed can enhance user experiences, enable real-time applications, and accelerate time to output.

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For executives, GPT-4o’s capabilities open up new possibilities for leveraging AI across various business functions, from content creation and data analysis to customer service and product development. It’s more human than its predecessors and designed to engage in ways that are also more human.

Its multimodal nature allows for more natural and engaging interactions, while its increased context window and knowledge base enable more comprehensive and informed decision-making. Additionally, the cost reductions make it more accessible for enterprises to adopt and scale AI solutions powered by GPT-4o.

Here are some creative ways people are already building on ChatGPT-40.

https://x.com/hey_madni/status/179072...

That’s your latest AInsights, making sense of ChatGPT-4o to save you time and help spark new ideas at work!

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AInsights: Microsoft Developing Its Own AI Model with MAI-1; Serves as a Competitive Lesson for All Businesses

AInsights: Your executive-level insights on the latest in generative AI

Microsoft is perhaps building one of the most prolific genAI investment portfolios of any company out there. The company is a deep investor ($10 billion) in OpenAI. OpenAI not only powers ChatGPT, but also Microsoft’s Copilot. Microsoft recently invested in French startup Mistral. The company also just pseudo-acquired Inflection AI, appointing co-founder Mustafa Suleyman as its CEO of consumer AI.

Compare this to Apple, one of most innovative companies in the world, who let the genAI revolution pass it by. In fact, after exploring ChatGPT, Apple executives believe Siri feels antiquated in comparison, warranting an urgent M&A or partnership strategy to compete.

Now, Microsoft is reportedly working on a new large-scale AI language model called MAI-1 according to The Information. The effort is led by Suleyman. Just as a reminder, Microsoft acquired Inflection’s IP rights and hired most of its staff, including Suleyman, for $650 million in March.

MAI-1 is Microsoft’s first large-scale in-house AI model, marking a departure from its previous reliance on OpenAI’s models. With around 500 billion parameters, it is designed to compete with industry leaders like OpenAI’s GPT-4 (over 1 trillion parameters) and Meta’s Llama 2 models (up to 70 billion parameters).

The pressure may be in part due to its position in the market as less than self-reliant. This comes after internal emails revealed concerns about Microsoft’s lack of progress in AI compared to competitors like Google and OpenAI.

For executives, Microsoft’s move highlights the strategic importance of investing in AI and the need to stay competitive in this rapidly evolving space. It also emphasizes the value of acquiring top AI talent and leveraging strategic acquisitions to accelerate in-house AI development. As the AI arms race continues, executives must carefully navigate the ethical and legal challenges while capitalizing on the opportunities presented by these transformative technologies.

These are lessons for all companies leaning on AI to accelerate business transformation and growth. If Apple and Microsoft are pressured to innovate, imagine where you company is on the spectrum of evolution.

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X: The Experience When Business Meets Design Named to Best Customer Experience Books of All Time List

When Brian Solis published X: The Experience When Business Meets Design, it was lauded as one of the best books to capture the zeitgeist of the digital revolution while laying out a practical blueprint to lead the future of modern customer experience design and innovation.

Even today, the book still leads the way forward, especially in an era of generative AI. And as testament to its endurance relevance and value, Bookauthority just announced X as one of the “Best Customer Experience Books of All Time!”

Additionally, X was and still is recognized for its stunning design, not common, at the time, amongst business books. In fact, X and its predecessor, WTF: What’s the Future of Business – Changing the Way Businesses Create Experiences, sparked a trend for business book design to earn a place both on bookshelves, lobbies, and coffee tables.

Here are a few other interesting facts you may not know about X…

Brian believed that for X to be taken seriously as a book about experience innovation that the book itself had to be an experience.

Because the book explores how digital and mobile are transforming customer expectations and as a result, customer journeys, the book was designed as an “analog app.” It doesn’t feature a traditional table of contents. It is organized by contextual themes vs linear format. And, the balance of written and visual narratives reflect experiences on your favorite apps vs. traditional books. Brian’s inspiration was to create a book that today’s high school, digital-first, students could read intuitively.

The shape of X is formed after an iPad because a smartphone was too small.

X was designed in partnership between Brian and the amazing team at Mekanism.

X was supposed to follow Brian’s second solo book with Wiley, The End of Business as Usual. Instead, the publishers felt that the gap between themes was too great. Brian wrote WTF to bridge the gap. Originally intended as an e-book only, Brian used the exercise to experiment with designing a print book as an analog app. This helped set the stage for X.

The “X” on the cover is real. It’s layers of etched glass. To give it the lighting effects, the X was placed on its back on top of a TV screen, which was illuminated to create a spectrum of colors. The video below is the result!

If you read X, please share with your networks on X, LinkedIn, Facebook, Threads, TikTok! Please use this link to it references the list. Thank you!

Invite Brian as your next keynote speaker!

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AInsights: Everything You Need to Know About Google Gemini 1.5; Surpasses Anthropic, OpenAI, In Performance, For Now

AInsights: Your executive-level insights on the latest in generative AI

Google is making up for lost time in the AI race by following the age old Silicon Valley mantra, move fast and break things.

Google recently released Gemini 1.5, and it’s next level! This release dethrones Anthropic’s brief reign as leading foundation model. But by the time you read this, OpenAI will also have made an announcement about ChatGPT improvements. It’s now become a matter of perpetual leapfrogging, which benefits us as users, but makes it difficult to keep up! Note: I’ll follow up with a post about ChatGPT/DALL-E updates.

Here’s why it matters…

1 million tokens: It’s funny. I picture Dr. Evil raising his pinky to his mouth as he says, “1 million tokens.” Gemini 1.5 boasts a dramatically increased context window with the ability to process up to 1 million tokens. Think of tokens as inputs, i.e. words or parts of words, in a single context window. This is a massive increase from previous models like Gemini 1.0 (32k tokens) and GPT-4 (128k tokens). It also surpasses Anthropic’s context record at 200,000 tokens.

A 1 million token context window allows Gemini 1.5 to understand and process huge amounts of data. This unlocks multimodal super-prompting and higher caliber outputs. A 1 million token context window can support extremely long books, documents, scripts, codebases, video/audio files, specifically:

1 hour of video

11 hours of audio

30,000 lines of code

700,000 words of text

https://twitter.com/briansolis/status...

This long context capability enables entirely new use cases that were not possible before, like analyzing full books, long documents, or videos in their entirety.

Chrome Support: With Perplexity creeping into Google’s long-dominate grasp on internet search (more about the future of search here), Google is at least integrating Gemini prompting directly in the Chrome browser. Here’s how to do it

https://twitter.com/briansolis/status...

More countries, more languages supported: Gemini 1.5 is available in 100 additional countries and now offers support for 9 additional languages. Languages supported include English, Japanese, and Korean: Arabic, Bengali, Bulgarian, Chinese (simplified and traditional), Croatian, Czech, Danish, Dutch, Estonian, Finnish, French, German, Greek, Hebrew, Hindi, Hungarian, Indonesian, Italian, Latvian, Lithuanian, Norwegian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovenian, Spanish, Swahili, Swedish, Thai, Turkish, Ukrainian, Vietnamese.

Google has put Gemini 1.5 through rigorous safety evaluations to analyze potential risks and harms before release. Novel safety testing techniques were developed specifically for 1.5’s long context capabilities.

That’s your AInsights in a snapshot to help you make sense of Google’s latest genAI news.

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Brian Solis to Explore the Future of Customer Experience Innovation at CX Midwest May 2024

Brian Solis will keynote CX Midwest on 14 May, 2024.

Brian’s keynote is titled, “Experience Innovation: The Rise of Generation Novel and the New CX Imperative.”

Description: Brian Solis is a world-leading digital anthropologist, best-selling author, and innovator in experience design. His research went into overdrive these last few years, combining the evolution of digital, mobile and social with the incredible effects of the pandemic, and now, how it all converges with AI, spatial computing! In this eye-opening presentation, Brian will share his insights into the state and future of experience design and how the emergence of a new generation of consumers need you to reimagine CX not as customer experience, but as the customer’s experience.

For those who don’t know, Brian is considered as one of the most influential pioneers in CX innovation. His book, X: The Experience When Business Meets Design, is considered the book on the subject. In fact, it’s been named to the list of “Best Customer Experience Books of All Time,” according to BookAuthority!

Book Brian to speak! Learn more here.

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Top 20 LinkedIn Influencers to Follow

Brian Solis was named in Insidea’s “Top 20 LinkedIn Influencers to Follow.” It’s an important list, so please take a look at the others to make the list…you’ll be smarter for it!

As the world’s premier professional networking platform, LinkedIn hosts a myriad of thought leaders, industry pioneers, and mavens who constantly share their wisdom, experiences, and forecasts about the business realm. But with millions of users vying for your attention, whom should you really tune into? To streamline your feed and ensure it’s valuable, we’ve curated a list of the top 20 LinkedIn influencers you should follow today. Dive in and prepare to be inspired, educated, and motivated.

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AInsights: Microsoft’s VASA-1 Model Uses AI to Create Hyper-Realistic Digital Twins Using a Picture and Voice Sample

AInsights: Executive-level insights on the latest in generative AI

Just when you’ve seen it all, there’s always something new that will surprise you, almost to the point, where you may lose the magic of surprise. We live in some incredible times, don’t we? As OpenAI co-founder and CEO Sam Altman said recently, “This is the most interesting year in human history, except for all future years.”

Well, I just read a research paper published by Microsoft Asia that blew my mind. And as you can imagine, it takes a lot to blow me away!

The paper essentially introduces what it calls the VASA framework for generating lifelike talking faces with “visual affective skills” (VAS).

Its first iteration, VASA-1, is a real-time, audio-driven talking face generation technology. It can create lifelike animated faces that closely match the speaker’s voice and facial movements, with, get this, single portrait picture, a same of speech audio, control signals such as main eye gaze direction and head distance, and emotion offsets, create a real-time hyper-realistic talking head video…all with scarily convincing gestures.

Unless you knew the person, and even then, it would be difficult for the untrained eye to detect that they were watching a machine-produced video (or in some cases, a deepfake).

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Certainly, Microsoft Research is exploring the boundaries for what’s possible with the best of intentions. So, in this piece, let’s focus on this technology with that perspective. From that point of view, key benefits and use cases of VASA-1 include:

Highly realistic and natural-looking animated faces: VASA-1 can generate talking faces that are indistinguishable from real people, enabling more immersive and engaging virtual experiences.

Real-time performance: The system can produce the animated faces in real-time, allowing for seamless integration into interactive applications, gaming, and video conferencing.

Broad applicability: VASA-1 has potential use cases in areas such as virtual assistants, video games, online education, and telepresence, where lifelike animated characters can enhance the user experience.

Potentially interesting use cases could include:

Virtual avatars and digital assistants: VASA-1 can be used to create virtual avatars and digital assistants that can engage in natural, human-like conversations. These avatars could be used in video conferencing, customer service, education, and entertainment applications to provide a more immersive and engaging experience.

Dubbing and lip-syncing: The ability to accurately synchronize facial movements with audio can be leveraged for dubbing foreign language content or creating lip-synced animations. This could streamline the localization process and enable more seamless multilingual experiences

Telepresence and remote collaboration: It can enhance remote communication and collaboration, allowing participants to maintain eye contact and perceive non-verbal cues as if they were physically present.

Synthetic media creation: VASA-1 could generate create highly realistic synthetic media, such as virtual news anchors or digital characters in films and games. This could open up new creative possibilities and streamline content production workflows.

Accessibility and inclusion: VASA-1 could improve accessibility for individuals with hearing or speech impairments, providing them with more natural and engaging communication experiences.

Microsoft Research Asia: Sicheng Xu*, Guojun Chen*, Yu-Xiao Guo*, Jiaolong Yang*‡, Chong Li, Zhenyu Zang, Yizhong Zhang, Xin Tong, Baining Guo Microsoft Research Asia *Equal Contributions ‡Corresponding Author: jiaoyan@microsoft.com

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AInsights: Meta’s Llama 3 LLM Redefines the Limits of Artificial Intelligence and Makes Meta One of the Leading AI Players

Created by Meta AI

Your AInsights: Executive-level insights on the latest in generative AI…

Meta released its Llama 3 Large Language Model (LLM), serving as the foundation for Meta AI. Furthermore, Meta is making Llama 3 open source for other third-party developers to use, modify, and distribute for research and commercial purposes, without any licensing fees or restrictions. More on that in a bit.

Meta AI serves as the AI engine for Messenger, Instagram, Facebook, as well as my go-to sunglasses created in partnership with Ray-Ban.

Mark Zuckerberg announced the news on Threads.

“We’re upgrading Meta AI with our new state-of-the-art Llama 3 AI model, which we’re open sourcing,” Zuckerberg posted. “With this new model, we believe Meta AI is now the most intelligent AI assistant that you can freely use.”

Meta also introduced a free website designed to compete (and look like) OpenAI’s ChatGPT, available at Meta.AI. Note, the service is free currently, but asks you to login in with your Facebook account. You can bypass this for now, though if you do log in, you are contributing toward training LLAMA 4 and beyond, based on your data and activity. This isn’t new for Facebook or any social media company, as you, and me, as users, have always been the product, the training grounds, and the byproduct of social algorithms.

Like ChatGPT, you can prompt via text for responses and also “imagine” images for Meta.AI to create for you. What’s cool about the image imagination (creation) process, it offers a real-time preview as you’re prompting. Compare this to say, ChatGPT or Google Gemini, where you have to wait for the image to be generated in order to fine tune the prompt. What’s more, users can also animate images to product short MP4 videos. Interestingly, all content is watermarked. And similarly, Meta.AI will also generate a playback video of your creation process.

All-in-all, the performance and capabilities race between Claude, ChatGPT, Gemini, Perplexity, et al, benefits us the users, as genAI is like the Wild West right now. We get to test the highest performer, at low costs or no costs, until the dust settles a bit more.

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What sets Llama 3 apart are its performance claims. Llama 3 introduces new models with 8 billion and 70 billion parameters, which demonstrate notable  improvements in reasoning and code generation capabilities. This aligns with industry benchmarks for advanced performance.

The number of parameters in a large language model like Llama 3 is a measure of the model’s size and complexity. More parameters generally allow the model to capture more intricate patterns and relationships in the training data, leading to improved performance on various tasks.

Unlike many other prominent LLMs like GPT-4 and Google’s Gemini which are proprietary, Llama 3 is freely available for research and commercial purposes. This open-source accessibility fuels innovation and collaboration within the AI community.

Meta is developing multimodal versions of Llama 3 that can work with various modalities like images, handwritten text, video, and audio clips, expanding its potential applications. For example, with the Meta Ray-Ban glasses, users can activate the camera and prompt, “hey Meta” to recognize an object, translate signage and text, even in different languages, and create text

Multilingual training is integrated into versions of Llama 3, enabling it to handle multiple languages effectively.

It’s reported that Meta is also training a 400 billion parameter version of Llama 3, showcasing its scalability to handle even larger and more complex models.

The “Instruct” versions of Llama 3 (8B-Instruct and 70B-Instruct) have been fine-tuned to better follow human instructions, making them more suitable for conversational AI applications.

Like with any model, accuracy and biases are always a concern. This is true with all AI chatbots. Sometimes, inaccurate results can have significant impacts though.

Nonetheless, Zuckerberg expects Meta AI to be “the most used and best AI assistant in the world.”  With integration into some of the world’s most utilized social media and messaging platforms, his install base is certainly there.

Disclaimer: Meta.ai drafted half of this story’s headline. It still needed a human touch.

This is your latest executive-level dose of AInsights. Now, go out there and be the expert everyone around you needs!

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If you’d like to join my master mailing list for news and events, please follow, a Quantum of Solis.

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AInsights: Perplexity AI is Now a Unicorn, Counts Jeff Bezos as an Investor, and Releases Enterprise Pro

Source: Perplexity

AInsights: Executive-level insights on the latest in generative AI…

Perplexity AI announced that it raised a whopping $62.7M+ at a valuation of 1.04 billion, led by Daniel Gross, former head of AI at Y Combinator. This officially makes Perplexity the latest minted Unicorn. Other investors include a who’s who list of industry leaders, Stan Druckenmiller, NVIDIA, Jeff Bezos, Tobi Lutke, Garry Tan, Andrej Karpathy, Dylan Field, Elad Gil, Nat Friedman, IVP, NEA, Jakob Uszkoreit, Naval Ravikant, Brad Gerstner, and Lip-Bu Tan.

Perplexity isn’t just another AI chatbot. It’s an entirely new answers engine that offers a glimpse of the future of intelligent search. I recently explored how Perplexity and AI are even threatening Google’s search business. This could be one of the reasons that Perplexity’s valuation has doubled in three months.

Excited to announce we've raised 62.7M$ at 1.04B$ valuation, led by Daniel Gross, along with Stan Druckenmiller, NVIDIA, Jeff Bezos, Tobi Lutke, Garry Tan, Andrej Karpathy, Dylan Field, Elad Gil, Nat Friedman, IVP, NEA, Jakob Uszkoreit, Naval Ravikant, Brad Gerstner, and Lip-Bu… pic.twitter.com/h0a986t4Md

— Aravind Srinivas (@AravSrinivas) April 23, 2024

Additionally, Perplexity launched Enterprise Pro, designed to keep work and data secure and private.

How does it work?

Think about your day-to-day search experience today. Typically when you search, you become the “answer filter,” browsing through SEO-manipulated or spammy websites full of affiliated links, all meant to boot their visibility, not the most relevant information. Perplexity streamlines search for everyday users and now, enterprise employees to help them save time while improving output.

Perplexity’s answer engine browses the internet in real time and provides complete, verifiable answers with citations (I love this part as I drill down into each for further context). Perplexity also provides multimedia-enriched answers that include charts, videos, and images.

In a statement, Databricks CEO Ali Ghodsi shared how Perplexity powers his teams, “Perplexity Enterprise Pro has allowed Databricks to substantially accelerate R&D, making it easier for our engineering, marketing, and sales teams to execute faster. We estimate it helps our team save 5k working hours monthly.”

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So what is an answers engine exactly? If you think about about how you use Google for more sophisticated or specific searches, you may often ask it questions versus inputting keywords. Smart marketers practice “keyword anthropology” to understand the questions people are asking to then optimize their pages against those searches. This leaves users having to become a human filter to search, scroll, click, and most likely, refine the search and repeat. This was just business as usual.

With Perplexity, it takes your prompt to then analyze potential results against trusted or regarded sources providing output that better aligns with your search criteria. The results are also footnoted if you’d like to dive deeper for context. More so, prompt-based searched facilitate prompt-based layers. You can dive deeper to further unpack the answers to help you steer your quest.

Enterprise Pro aims to offer a rich search experience for its business users.

Here’s how standout companies use Perplexity…

Product teams at Zoom use Perplexity’s Focus functionality for targeted search.

HP’s salesforce taps into Perplexity for rapid, in-depth prospect research, helping them to craft compelling pitches, which expedites the sales process.

Innovation attorneys at Latham & Watkins are piloting Perplexity to conduct targeted research.

Health editorial teams at Thrive Global are creating validated behavior change microsteps based on the latest peer-reviewed science.

Data teams at the Cleveland Cavaliers research ticket sales trends and do partnership prospecting.

Strategy teams at Paytm draft market landscape insights to inform their roadmaps.

Marketing and product teams at Amplitude use Perplexity to draft market landscape insights.

Below is the pitch deck for Perplexity Pro courtesy of PitchDeckGuy.

And here you are. You’re up to date on the trends I’m paying attention too. Now share this with key players around you to become a trusted resource in your community!

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AInsights: Reid Hoffman Interviews His AI Digital Twin and It’s Both Creepy and Mind-Blowing

Your AInsights: Executive-level insights on the latest in generative AI…

You may know Reid Hoffman as the co-founder and executive chairman of LinkedIn. He’s also a prolific investor and author, writing a book with my friend Chris Yeh, one I refer a lot to founders, Blitzscaling.

Hoffman recently recorded an interview with Reid AI, his digital twin, and it is wild! It’s innovative while also blurring the line between fantastical and the uncanny valley.

Like ChatGPT itself, Reid AI was trained on a large language model (LLM), but instead focused on Reid’s writings, speeches, interviews, podcasts, appearances, and books. Reid AI’s digital brain is not only trained on his work, but also his mannerisms, voice, conversational style, and appearance.

There’s even an awkward moment when Reid AI wipes his nose and then proceeds to wipe his hand on the table. And at times, Reid AI appears to breathe!

Hour One developed the regenerative AI models for the video and 11ElevenLabs worked on the audio.

“I think these avatars,” writes Hoffman, “when built thoughtfully, have the potential to act as mirrors to ourselves – ones that reflect back our own ideas and personality to examine and consider.”

More so, digital twins offer the ability to teach or mentor others, or to provide a virtual legacy for personalities to engage future generations . Just a couple of years ago, Soul Machines created a digital twin of golf legend Jack Nicklaus (aka the Golden Bear) to interact with fans or even offer advice to budding golfers.

At the same time, there are causes for concern as AI deepfakes have defrauded a bank for $25 million and most recently, a South Korean woman was scammed for $50k to a fake digital twin of Elon Musk.

While both incredible and controversial, this technology is inevitable however, and at some point in the near future, we’ll have the ability to create digital twins of our loved ones much in the same way. For this reason, future generations will learn to capture the work, words, and all creations to thoroughly train models to best represent those they care about.

Also consider creating virtual markets populated with digital twins of customers and aspirational prospects. The opportunity to sample marketing or service concepts, test market PoCs, experiment with customer and employee journeys, or assess competitive products.

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The significance of Reid Hoffman interviewing his AI-generated digital twin demonstrates how far we’ve come in the evolution of generative AI and its ability to recreate someone as an avatar in ways that could be indistinguishable from the real person…or from a real person.

In this case, Hoffman and team can test the capabilities of the AI system and how closely it can mirror his own thinking, behaviors, and responses. By challenging the AI with questions on topics like “blitzscaling” and AI regulation, Hoffman is evaluating how well the AI can formulate answers in a way that aligns with his own perspectives and communication style. It gets close, but it will also only get better.

The interview also provides Hoffman, and the rest of us, the opportunity to explore the ethical considerations around AI and deepfakes. He acknowledges the risks and dangers of this technology, while also recognizing its potential benefits.

By engaging with his AI twin, Hoffman is gaining firsthand experience on how this technology could disrupt and challenge individuals, including public figures like himself. This hands-on experiment likely informs his views on how to responsibly develop and regulate AI systems going forward.

The video also demonstrates the awareness and literacy we all need in being mindful of what’s real and what’s not. Additionally, it’s a call to tech companies to regulate their own tech and also develop tools to help the rest of the world identify deepfakes and potential bad actors

Enjoy the interview below!

Well, this is your latest AInsights on digital twins, deepfakes, and the crazy new world we’re living in. See you next time!

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