“Crypto is decentralizing, AI is centralizing. Or, if you want to frame it more ideologically, crypto is libertarian and AI is communist.” – Peter Thiel
AI-generated image Produced by DALL-E by OpenAI Labs Using the prompt: “Abundance vs. Self-expression”
AI and Crypto are diametrically opposed to each other, yet can complement each other in incredibly useful ways when joining forces. Maybe that’s true of most diametrically opposed forces? That’s a discussion for a different blog post.
Four differentiations to consider:
Control vs. Coordination
AI is top-down; strongest when information and control are centralized.
Crypto is bottom-up; strongest when information and coordination are decentralized.
Status Quo vs. Disruption
AI sustains the status quo and reinforces the strength of existing businesses.
Crypto disrupts existing business models and helps fringe efforts challenge existing businesses.
Conformity vs. Individualism
AI reinforces behavior in accordance with accepted conventions or standards.
Crypto increases privacy and empowers self-sovereignty.
Abundance vs. Self-expression
AI creates an abundance of media and machine-generated creations.
Crypto enables self-expression and verifies human identity.
Now that we’ve laid out how they differ, what are some ways they can work together?
Code Creation
Crypto projects – like any software development – rely on well-written computer code. AI is a useful tool for writing computer code. Tool is a key word here. AI is an incredibly powerful tool, but it does not (yet) replace the need for a human to properly utilize the tool.
One major weakness in AI-generated code is security; or a lack thereof. AI is going to suggest methods it finds within its data. As anyone who is one of the billions of people who has had their information compromised thanks to a security breach within a service they use, we know a lot of human-written code is susceptible to being hacked or exploited.
AI can be used to write code, then used to find exploits in AI-written code, then used to fix the found exploits, then be used to test again, and so on. What would take longer? Iterating through this process until the code is secure, or licking a Tootsie Pop until you find the center? Should we ask Mr. Owl?
Deepfakes
AI has gotten really good at generating deepfakes. Crypto (or simply blockchain technology) is being leveraged to create ways to prove authenticity and validate ownership.
We’d also love to discuss Zero Knowledge Machine Learning (ZKML) Proofs with you, and what they have to do with finding Waldo, but we’ll save that for another post.
Have any topics you’d like to learn more about? Please reach out to us and we’ll research it for you in a future blog post.
We offer – what we believe is – a more plausible reason than either of those beliefs. Maybe Musk’s “Everything App”, X, formerly known as Twitter, is aiming for Artificial Intelligence dominance over tech giants such as Facebook, Google, Microsoft, and Apple… combined. Crazy? Yes. But, so is a man who named his first child X Æ A-Xii, grouped his Tesla cars into four models: Model S, Model 3, Model X, and Model Y and sells the accompanying ‘S3XY’ hoodie, launched a Tesla Roadster into space playing David Bowie’s song “Space Oddity” on the radio with a mannequin – named “Starman” – in a spacesuit sitting in the driver’s seat, and launched Starlink – over 5,000 satellites (so far) – as part of an internet constellation operated by SpaceX, just to name a few (of many).
If you’d like us to post more on this Musk – X – AI theory, please let us know.
2. Should Artificial Intelligence now be called Alien Intelligence?
AI-generated image Produced by DALL-E by OpenAI Labs Using the prompt: “Alien intelligence dominates the new world”
If you are not yet familiar with Yuval Noah Harari, we recommend correcting this oversight.
To get us started, some definitions for consideration:
Artificial – made or produced by human beings rather than occurring naturally, especially as a copy of something natural.
Alien – a foreigner, especially one who is not a naturalized citizen of the country where they are living.
Natural – existing in or caused by nature; not made or caused by humankind.
Naturalized – (of a plant or animal) having become established and living wild in a region where it is not indigenous.
The term “Artificial Intelligence” was appropriate when first coined in 1956 by John McCarthy at the Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI). Human beings were creating intelligence that was not natural. However, we’ve come a long way since the early days of Neural Networks and Machine Learning.
Neural Networks and Machine Learning were inspired by the way the human brain is structured and the way humans learn. These days, machines are learning more from each other than their human creators. And they are discovering our methods can sometimes be primitive due to our biological limitations.
For – what is believed to be – the world’s oldest board game, Go, originating around 4,000 years ago, human design was not enough. AlphaGo started playing machine vs. machine (AlphaGo Zero vs. AlphaGo Lee) to improve its intelligence beyond anything a human could design.
If machines are now learning from other machines, and developing intelligence beyond our human brain’s comprehension, is their intelligence still artificial, or has it become alien?
“AI is an ‘alien intelligence’ that is as foreign to us as it is familiar, challenging the notion that AI will simply mimic human appearance or tasks.” – Yuval Noah Harari
Videos for continuing your Yuval Noah Harari journey
TIME did the heavy lifting here. They compiled a list of their 100 most influential people in AI; and even grouped them into four categories: Leaders, Innovators, Shapers, and Thinkers. We selected one from each category to highlight.
We selected Clément Delangue because his company has the best name – Hugging Face. Well, that and because we plan to discuss closed source (proprietary) AI vs. open source AI in a future post, and Hugging Face is an open source David attempting to go up against the big tech Goliaths.
We selected Kate because it’s important to keep in perspective the fact that the challenges and opportunities resulting from AI are global; not just something that affects us here in the U.S. where the largest tech firms exist. This young entrepreneur’s mission is to fix the critical issue facing many countries like Kenya: a lack of data.
We selected Verity because governments will play a huge role in the future of AI, and she understands the intersection between emerging technology and democracy. Verity says, “AI is too important just to be left to the AI community alone. It needs to be more widespread.” We at Data Directions agree with her.
We selected Max because he’s an old favorite of ours. We follow his “Future of Life Institute“, founded in 2014, and believe in its mission of “steering transformative technology towards benefitting life and away from extreme large-scale risks.” We also highly recommend reading his 2017 book, “Life 3.0“.
I have been a software developer for several years but I’m new to AI programming concepts. I use ChatGBT all the time and I’ve been reading about AI programming concepts. However, I tend to envision SQL solutions instead of AI solutions (If all you have is a hammer…). Most of my work has been web development, so I asked ChatGBT “how can web developers use AI to help clients?” and it gave me 15 use cases. For most of them, it ended with “…and then use AI algorithms [to solve the problem]”. Not super helpful, but one that stood out to me was “Analyze Website and Online Presence”.
Analyze Website and Online Presence-
Examine competitors’ websites to understand their design, user experience, content quality, and functionality.
Study their social media presence, engagement levels, and the type of content they share.
If a reusable tool could be developed and automated with minimal code writing, then the harvested data would have greater value. I would be especially interested in how AI solutions could analyze “content quality” and “functionality”. A reusable AI tool like this, one that can analyze any competitor’s online presence would be a valuable tool for any business. Tools like these are starting to be developed and sold as we are entering a new era where AI tools can be found for any scenario and, ideally, work out of the box. It’s an exciting time for software development.
Short (20 min listen) with a Ai wrap up and then an full story.
It’s a daily routine to listen in my car. On a typical day I send myself a note to follow-up on an AI tool, writer, or other resource heard on the podcast.
Artificial Intelligence (AI) platforms and systems have revolutionized the way businesses operate by unlocking the potential of existing applications. These platforms provide a framework for developing and deploying AI-powered solutions, enabling organizations to leverage the power ofmachine learning,natural language processing, and other AI technologies. With AI platforms, businesses can enhance their existing applications with intelligent capabilities, improving efficiency, accuracy, and decision-making processes.
AI platforms encompass a wide range of tools, frameworks, and libraries that enable developers to build and deploy AI models. These platforms provide a unified environment for data preparation, model training, deployment, and monitoring. They offer pre-built algorithms and APIs that simplify the development process and allow organizations to quickly incorporate AI into their existing applications.
By integrating AI into existing applications, businesses can unlock numerous benefits. One of the key advantages is improved efficiency. AI-powered automation can streamline repetitive tasks and free up valuable human resources for more complex work. For example, customer servicechatbots powered by natural language processing can handle common inquiries without human intervention, reducing response times and improving customer satisfaction.
Another benefit of AI platforms is enhanced accuracy. Machine learning algorithms can analyze vast amounts of data with precision and uncover patterns that humans might overlook. This enables businesses to makedata-driven decisions based on accurate insights. For instance, financial institutions can use AI models to detect fraudulent transactions in real-time by analyzing historical transaction data.
AI platforms empower organizations to make smarter decisions by leveragingpredictive analytics capabilities. By analyzing historical data patterns and identifying trends, businesses can forecast future outcomes with greater accuracy. This helps in strategic planning and resource allocation. For example, demand forecasting models powered by AI can help retailers optimize inventory levels based on predicted consumer demand.
Meta models play a crucial role in enhancing the capabilities of AI platforms. These are higher-level models that combine multiple individual models to solve complex problems or make predictions across different domains. Meta models enable better generalization by leveraging the strengths of individual models and compensating for their weaknesses. By utilizing meta models, businesses can achieve more accurate predictions and improve the overall performance of their AI applications.
One notable AI platform in the market is Microsoft’s Azure AI platform. It offers a comprehensive suite of AI tools and services that cater to various business needs. The platform includes pre-built AI models, such ascomputer vision andspeech recognition, which can be easily integrated into existing applications. Microsoft Azure also provides powerful machine learning capabilities, allowing organizations to build custom AI models tailored to their specific requirements.
Enhancing Existing Applications with AI
With the rapid advancement of artificial intelligence (AI) technology, businesses are increasingly exploring ways to integrate AI into their existing applications. By doing so, they can unlock the full potential of these applications and provide enhanced functionality and user experiences. The benefits of integrating AI into existing applications are numerous and can revolutionize the way businesses operate.
One of the key benefits of incorporating AI into existing applications is improved decision-making capabilities. AI algorithms can analyze vast amounts of data in real-time, enabling businesses to make more informed decisions quickly. For example, an e-commerce application can utilize AI to analyze customer preferences and purchasing patterns to provide personalized product recommendations. This not only enhances the user experience but also increases the likelihood of conversions and customer satisfaction.
In addition to improved decision-making, AI can also enhance the functionality of existing applications. Natural Language Processing (NLP) algorithms, for instance, can be integrated into chatbot applications to enable more accurate and efficient customer interactions. These chatbots can understand and respond to user queries in a conversational manner, providing instant support and reducing the need for human intervention. This not only improves customer service but also frees up valuable resources within a business.
AI can optimize existing applications by automating repetitive tasks. Machine learning algorithms can be trained to perform tasks that would otherwise require manual intervention, such as data entry or content moderation. This automation not only saves time but also reduces errors and improves overall efficiency. For example, an inventory management application can use machine learning algorithms to automatically update stock levels based on sales data, ensuring accurate inventory management without manual input.
Another significant benefit of integrating AI into existing applications is the ability to leverage predictive analytics. By analyzing historical data using machine learning algorithms, businesses can predict future trends and outcomes with a high degree of accuracy. For instance, a financial application could use predictive analytics to forecast market trends or identify potential investment opportunities. This empowers businesses with valuable insights that can drive strategic decision-making and improve overall performance.
Implementing AI in existing applications does come with its challenges. Businesses need to consider factors such as data privacy, ethics, and the potential impact on jobs. It is crucial to ensure that data used for AI algorithms is collected and stored securely, respecting user privacy rights. Ethical considerations must also be taken into account when designing AI-powered applications to avoid biases or discriminatory outcomes. Additionally, businesses should proactively address concerns about job displacement by retraining employees and creating new roles that leverage the benefits of AI technology.
