Tag: Artificial Inteligence

Chapter 6: Motivation, Psychology, and Productivity

October 3, 2023October 1, 2023by jasonnash101Leave a comment

Achieving the ambitious 10x productivity goal involves understanding the intricacies of human psychology and motivation. This article explores how various psychological theories and practices can be harnessed to drive significant performance improvements.

Traditional vs. Modern Motivators

Daniel Pink’s book “Drive: The Surprising Truth About What Motivates Us” challenges traditional motivators like rewards and punishments. He proposes three key elements for modern motivation: autonomy, mastery, and purpose.

Autonomy: Empowering employees to make decisions and manage their tasks fosters a sense of ownership and responsibility, elevating productivity.
Mastery: Opportunities for skill enhancement and personal growth can motivate employees to excel.
Purpose: Aligning individual tasks with organisational goals helps employees see the bigger picture, driving them to contribute more effectively.

Organisational Psychology

Organisations increasingly hire psychologists to cultivate a culture conducive to high productivity. These experts leverage theories like Maslow’s hierarchy of needs and cutting-edge tools like MRI scanners to study motivational states.

Intrinsic vs. Extrinsic Motivation Research shows that intrinsic motivation, driven by internal factors, often yields better productivity than extrinsic motivators like rewards. Emotional engagement often results in higher levels of job satisfaction and output.
Emotional Impact on Productivity Positive emotions such as joy or excitement can boost creativity and engagement. Conversely, negative emotions like stress can hinder productivity, leading to burnout.
Richard Finnegan’s Insights Finnegan emphasises the role of leadership and organisational culture in driving productivity. Engaged employees are more likely to be productive, and it’s up to the leaders to foster that engagement through effective vision, objectives and key results focused on meaningful outcomes and not just busy work.

The Future: AI & Psychology

From route planning to voice recognition, AI is increasingly woven into our daily lives, shaping our interactions and decisions.

AI’s Role in 10x Productivity: Symbiosis of AI and Humans

The future likely involves a combination of human decision-making and AI algorithms, potentially leading to more successful and efficient outcomes.

Advanced AI can help automate tasks, from document sorting to complex decision-making, contributing to the 10x productivity vision. Explainable AI will make these processes transparent and trustworthy.

New Breed of Productivity Apps

From Slack, MS Teams, AirTable to Monday.com, new tools promise productivity but often deliver distraction. The future might see AI-driven apps that augment human capabilities without causing information overload through communication channel multiplication.

Understanding the psychology behind motivation and productivity is crucial for any organisation aiming for a 10x increase in performance. From modern theories to technological advancements, various tools and strategies can be employed to navigate the complex landscape of human motivation. The key lies in aligning these factors effectively to propel the organisation toward its ambitious goals.

Embracing AI and Smart Agents

July 27, 2023July 17, 2023by jasonnash101Leave a comment

The technology landscape is evolving rapidly, with AI and large language models (LLMs) reshaping how businesses operate. NVIDIA’s recent announcement of AI Foundations, a cloud service offering that enables businesses to build, refine, and operate custom LLMs and generative AI models using proprietary data, highlights the growing importance of AI in the corporate world.

Just as websites transitioned from being a novelty in the early days of the internet to an essential component of any business, AI is poised to become an indispensable tool for organisations across industries. One area where AI’s impact is particularly evident is the emergence of smart agents, which are transforming both internal processes and customer-facing interactions.

Internal Smart Agents (internal like Intranet):

Process automation: Streamline repetitive tasks like data entry and report generation.
Knowledge management: Organise and manage internal knowledge for quick access.
Decision support: Analyze data and provide insights for informed decision-making.
Employee onboarding and training: Offer personalised guidance and integration for new hires.
Virtual assistants: Support employees in daily tasks, schedule management, and reminders.
AI board members and strategic advisors: Utilize AI to identify trends, assess risks, and provide unbiased insights for strategic decisions, such as the AI board member “VITAL” developed by Deep Knowledge Ventures.

External Smart Agents (Like a web page):

Customer support: Provide instant, personalised assistance for customer inquiries and issues.
Sales and marketing: Guide potential customers through purchasing with relevant product suggestions.
Personalised recommendations: Enhance the customer experience with tailored product or service recommendations.
Content creation and curation: Generate personalised content based on customer interests.
Social media management: Engage with customers on social platforms and manage online communities.
NVIDIA’s AI Foundations, along with similar advancements, make it easier for businesses to harness the power of AI and LLMs to create smart agents tailored to their specific needs. These technologies offer a competitive edge, enabling companies to optimise processes, enhance customer experiences, and drive innovation.

As AI progresses, forward-thinking businesses must embrace these transformative tools to stay ahead and remain competitive. Failure to do so will mean a non-competitive cost model and, ultimately, business failure.

Exploring Frankenstein Products in the Age of Artificial Intelligence

July 12, 2023July 13, 2023by jasonnash101Leave a comment

What is a Frankenstein Product: Overview

I’m not the first to have used the term “Frankenstein Product” which is often used to describe a product that is a mishmash of features hastily stitched together without a clear vision or purpose. These products often result from a lack of understanding of the customer’s needs or an overzealous attempt to incorporate every possible feature into a single product. The result is a confusing product, difficult to use, and often fails to meet the customer’s needs. It also becomes bloatware difficult to QA, manage and support. For buys, you can also tell these products if suppliers are unwilling to let you have a free trial or if the deployment is measured in months instead of days or weeks!

In the Artificial Intelligence (AI) age, the risk of creating Frankenstein Products is even greater. With the vast array of AI technologies available, it’s tempting for businesses to incorporate as many features as possible into their products. However, without a clear understanding of the customer’s needs and why the customer will use your to-do list over the competition’s; and a strategic approach to product development, these products can quickly become unwieldy and ineffective. I could name some examples, but maybe that is better for people to leave in the comments.

The term “Frankenstein Product” is derived from Mary Shelley’s novel Frankenstein, in which a scientist creates a monster by stitching together parts from various bodies. Just like the monster in the novel, Frankenstein Products are often seen as abominations, lacking in coherence and functionality.

Why AI will lead to an explosion of Frankenstein Products

AI’s emergence has revolutionized product development. It enables the analysis of massive data volumes, prediction of customer behavior, task automation, and personalization of experiences. For developers, AI enhances speed, bolsters QA procedures, and aids in code refactoring. However, this acceleration could lead to an overabundance of features. Without collaboration between a product manager and a product designer skilled in UX and CX, this risk escalates.

Speed does not equate to value if quality or usefulness is missing; a principle acknowledged in Agile, where building irrelevant or unused features quickly is the most significant form of waste, moves you further from the goal of product-market fit. Hence, the emphasis should be on outcomes rather than output when creating products that customers will love.

The problem lies in the fact that AI is not a one-size-fits-all solution. Each AI technology has its own strengths and weaknesses, and not all of them will be relevant or beneficial to every product. Furthermore, the integration of AI technologies into a product requires a deep understanding of the technology and its implications. Without this understanding, businesses run the risk of creating products that are confusing, difficult to use, and fail to deliver on their promises.

Moreover, the rapid pace of AI development means that new technologies are constantly emerging. This can lead to a constant cycle of adding and removing features, resulting in a product that is constantly changing and lacks stability.

How to Avoid Frankenstein’s Monster: Product Market Fit

To avoid creating a Frankenstein Product, businesses need to focus on achieving product-market fit. This means developing a product that meets the needs of specific customer segments and creates value for them which in turn creates value for the business building them at a price that the market is willing to pay.

Achieving product-market fit requires deeply understanding the customer’s needs and desires. This can be achieved through customer interviews, surveys, and market research. By understanding the customer’s pain points, businesses can develop a product that provides a solution to these problems. To do this good product managers and product designers need to spend a minimum of 20% of their time interviewing customers. Yes, that one whole day a week? Are you spending that much time a week interested in the comments below?

Know your customer’s Jobs-to-be-done.

The final guard against creating Frankenstein Products is deeply understanding the customer’s Jobs-to-be-done (JTBD). The JTBD framework is a way of looking at customer needs not in terms of products or services, but the jobs that customers need to get done. By understanding the customer’s JTBD, businesses can develop products that solve these jobs. This can help ensure the product is relevant and valuable to the customer. Mapping your product blue ocean strategy canvas can also help you avoid the monster.

The concept of Jobs-to-be-Done (JTBD) was popularized by Clayton M. Christensen, a Harvard Business School professor, in his book “The Innovator’s Solution: Creating and Sustaining Successful Growth,” which was published in 2003. The book was co-authored with Michael E. Raynor.

The JTBD theory is a framework for understanding what causes consumers to adopt new products or services. According to Christensen, customers don’t simply buy products or services; they “hire” them to perform a job that they need to get done. This idea has influenced a wide range of innovation and product development practices.

In conclusion, while the advent of AI has opened up a world of possibilities for product development, it has also increased the risk of creating Frankenstein Products. By focusing on achieving product-market fit, understanding the customer’s JTBD, and being strategic in using AI technologies, businesses can avoid this pitfall and create valuable, relevant, and loved products. Next time I will wring about Zombie products, why they exist and what to do about them. Tip: Traditional projects have a lot to answer for…

AI Unleashed: Maximizing Business Value with OpenAI, LangChain, Pinecone, and Neo4J

May 29, 2023May 30, 2023by jasonnash101Leave a comment

In the rapidly evolving digital landscape, the potential for artificial intelligence (AI) to revolutionize business practices is clear. Leading the charge are technologies like OpenAI, LangChain, Pinecone, and Neo4J – powerful tools capable of constructing highly efficient personal AI assistants. #AI #OpenAI #LangChain #Pinecone #Neo4J

I’ve recently been rereading about the Renaissance. Although I did a history A-level, it’s been a few years. One standout item is the creativity that occurred in a relatively short period of time. Today in business, we’re obsessed with diversity, but it was diversity that ultimately resulted in such an explosion of creativity in the Renaissance period. It’s this amalgamation of ideas that has me excited for the future of AI training. The new large language models built on even larger more diverse sets of data I believe will result in real breakthroughs. Greater than what we’ve already seen in the next few years – DeepMind has already given us, AlphaFold. But what lies around the corner will be even more exciting. To leverage this business leaders need to be more technically aware and willing to understand technologies.

Because AI assistants will not only bolster productivity but also serve as vital assets in customer value creation. They can automate routine tasks, provide critical insights, and even retain a history of interactions for intelligent search capabilities. The beauty of such systems lies in their ability to learn and adapt, making them invaluable allies in the pursuit of business excellence. #BusinessTransformation #ValueCreation

However, to fully harness the potential of these technologies, a basic understanding is crucial. This knowledge empowers, CTOs, and Product Managers to make informed decisions and strategically incorporate these tools into groundbreaking capabilitiesinto their operations. It’s not about becoming a technical expert, but rather understanding enough to appreciate the capabilities and potential applications of these technologies. #Leadership #DecisionMaking

For example, OpenAI’s GPT-3 can generate human-like text, making it a powerful tool for customer service or content creation. LangChain facilitates props and chain of thought reasoning, a boon for supporting better output with less hallucinations. Pinecone, a vector database, excels at handling complex, high-dimensional data, while Neo4J, a graph database, is exceptional for mapping relationships and finding patterns.

Imagine having a personal AI assistant that not only responds to customer queries in real time but also leverages past interactions to provide personalized responses. It could analyse sentiment to predict customer behavior and recommend actions to improve customer satisfaction. Such potential is no longer a distant dream, but a tangible reality within our grasp.

Understanding and using these technologies is not just about staying ahead in the digital race. It’s about transforming how we do business and unlocking unprecedented levels of value creation and 10x productivity. The future is here, but to leverage it you need to work with and engage the right tools and skills . #FutureIsNow #DigitalTransformation

10x Productivity and Engagement with AI-Generated Visuals and Voices

May 2, 2023April 25, 2023by jasonnash101Leave a comment

In this short blog post, I want to share my experience using two remarkable AI technologies: AI Automatic 1111 GUI and Eleven Labs speech tech. These tools can help you create stunning visual and audio content with minimal effort and cost.

Automatic 1111 GUI is a browser interface for Stable Diffusion, a deep learning model that can generate realistic images from text descriptions. You can use it to create anything from surreal paintings to photorealistic portraits, just by typing what you want to see. You can also edit existing images by sketching, inpainting, outpainting or upscaling them. AI Automatic 1111 GUI lets you choose from different models, adjust various parameters, clone or design new voices, and merge checkpoints. I have been using it to create all my recent blog post images.

Eleven Labs speech tech is a voice technology research company that develops the most compelling AI speech software for publishers and creators. Their Prime Voice AI platform can convert any text to speech in any voice and any emotion with unprecedented fidelity and context awareness. You can use it to voice news articles, newsletters, blogs, audiobooks, videos or games. You can also clone voices from surprisingly small samples or create entirely new synthetic voices from scratch. The authentic storytelling potential for this is significant and although It does not yet supports the nuance of Stephen Fry’s reading say Harry Potter. However, with a little effort and the creation of voices, I would image we are not that far away.

It’s truly amazing how these technologies can work together to create uber-personalization for an audience. I used AI Automatic 111 GUI to generate these images on my blog. It’s crazy what you can do with it for example these images are based on me having trained the model on some pictures of myself and if I ever wanted to know what I might look like as a woman; well know I know! The important thing to realize here is that they are not “photoshopped” they are totally computer generated.

I used Eleven Labs speech tech to clone my own voice from a 15-second recording it’s a bit bazar to hear yourself say something you have never said! But the potential for this is enormous. As a Dyslexic person who does not find reading a pleasure, I can see a host of user cases. For example, in the games industry, when playing a computer game, you could have the narrate spoken out loud in your own voice. Many AAA game have voice actors for large amounts of text, but the quests are still written and require the payer to read. I have also experimented having my blog read in my own voice the result was a personalized audio experience that sounded surprisingly just like me. It is of course, possible to combine Automatic 111 GUI and Eleven Labs tech along with some animation to combine the two.

Eleven Labs and Automatic 1111 GUI have the potential to be game-changers in the B2B, B2C, and B2B4C spaces, transforming industries in ways we’ve yet to fully imagine. As someone who began my career around the same time as the internet was emerging, I’ve witnessed first-hand the transformative power of technology. AI is already revolutionizing the way we work and create, with machine learning driving ever-faster improvements.

Businesses of all sizes need to embrace these new technologies and transition to an AI-powered future. Just as everyone was building a website in the early days of the internet, I believe that soon everyone will be shifting to an AI-powered agent. These agents can work 24/7, delivering a 10x productivity boost for businesses of all sizes. And for those Woking in marketing looking to create engaging content without spending too much time or money on production, these technologies are a must-have.

At Curious Cognition, we help businesses understand how AI technologies can be applied to create game-changing products and services and support a 10x productivity increase. If you’re interested in trying them out, visit their websites or contact me to schedule a call for an overview of what’s possible.

In my next article, I’ll be sharing my experimentation with an open-source project called Auto GTP, as well as two products: LangChain and Pinecone, which make the creation of intelligent agents possible today. Stay tuned for more insights on how AI is changing the game!