Sandy CarterContributor
I’m COO at Unstoppable Domains, a Web3 digital identity platform
I was recently engaged in a conversation about my work on Watson back in 2015 when a comment I received confused with me: “AI just started! Was ChatGPT created in 2015?” I realized then that many people didn’t realize the depth of AI history.
First of all, what is AI? Artificial Intelligence, a specialty within computer science, focuses on creating systems that replicate human intelligence and problem-solving abilities. These systems learn from data, process information, and refine their performance over time, distinguishing them from conventional computer programs that require human intervention for improvement.
The landscape of artificial intelligence (AI) is a testament to the relentless pursuit of innovation by technologists that have shaped its trajectory. In this journey, key players have emerged, each contributing to the evolution of AI in unique and transformative ways.
The Way Back When
The history of AI can be traced back to the 1950s, when Alan Turing published “Computer Machinery and Intelligence,” introducing the Turing Test as a measure of computer intelligence. At the same time, John McCarthy, a “founding father” of AI, created LISP, the first programming language for AI research which is still used today
The 1970s saw significant milestones including the autonomous Stanford Cartnavigating a room full of chairs and the founding of the American Association of Artificial Intelligence, now known as the Association for the Advancement of Artificial Intelligence (AAAI).
The AI Winter: 1987-1993
A period of low interest and funding in AI followed due to setbacks in the machine market and expert systems. Despite decreased funding, the early 90s brought AI into everyday life with innovations like the Roomba and speech recognition software.
The surge in interest was followed by a new funding for research, which allowed even more progress to be made.
IMPACT IBM (1997-2011)
IBM started its AI adventure when Deep Blue beat the world chess champion, Gary Kasparov, in a highly-publicized match in 1977, becoming the first program to beat a human chess champion. In 2011, IBM then created Watson, a Question Answering (QA) systems. Watson went on to win Jeopardy! against two former champions in a televised game. Recognized globally for this groundbreaking performance on Jeopardy! Watson showcased the transformative potential of cognitive computing.
Innovation in this period revolutionized industries such as healthcare, finance, customer service, and research. In the healthcare sector, Watson’s cognitive capabilities proved instrumental for medical professionals, offering support in diagnosing and treating complex diseases. By analyzing medical records, research papers, and patient data, it facilitated precision medicine practices, empowering healthcare practitioners with valuable insights into potential treatment options. Watson’s transformative impact extended to customer service, where it reshaped interactions through the provision of intelligent virtual assistants.
Watson’s influence also reached the realm of research and development, empowering researchers to analyze vast amounts of scientific literature. This catalyzed the discovery of new insights and potential breakthroughs by uncovering patterns, correlations, and solutions hidden within extensive datasets.
“Watson was one of the first usable AI engines for the Enterprise,” said Arvind Krishna, CEO of IBM. “IBM continues to drive innovation in AI and Generative AI to help our customers move forward.”
Watson’s legacy is profound, showcasing the formidable power of AI in understanding human language, processing vast datasets, and delivering valuable insights across multiple industries. Its pioneering work in natural language processing and cognitive computing set the stage for subsequent innovations like ChatGPT, marking a transformative era in the evolution of artificial intelligence. IBM continues to innovate in AI today.
The Assistants and Beyond: Amazon AMZN and Apple AAPL(2011-2014)
Amazon’s AI foray with Alexa and Apple’s Siri both marked significant leaps in human-computer interaction. These voice-controlled virtual assistants transformed how users can access information, control environments, and shop online, showcasing AI’s potential for daily life improvement.
Beyond voice assistance, Amazon leverages AI for personalized recommendations on its e-commerce platform, enhancing the customer shopping experience. Additionally, the company’s robust cloud computing service, Amazon Web Services (AWS), provides scalable and efficient infrastructure for AI development, enabling businesses and developers to leverage cutting-edge machine learning capabilities. Amazon’s commitment to advancing AI technologies aligns with its vision of making intelligent and intuitive computing accessible to users in various aspects of their daily lives, from the living room to the online marketplace.
Google GOOG: Deep Learning Breakthroughs (2012-2019)
Google, synonymous with innovation, has been a driving force in AI research. The development of DeepMind, a subsidiary of Google, marked a turning point with groundbreaking achievements in deep learning and reinforcement learning. For example, two researchers from Google (Jeff Dean and Andrew Ng) trained a neural network to recognize cats by showing unlabeled images with no background information.
Google’s commitment to democratizing AI is evident through TensorFlow, an open-source machine learning library empowering developers worldwide to create and deploy AI applications efficiently. Additionally, Google’s advancements in natural language processing, image recognition, and predictive algorithms have shaped the landscape of AI applications across diverse domains with Google Search, Photos, and Assistant demonstrating a commitment to enhancing user experiences and making AI an integral part of daily life.
OpenAI: Expanding the Horizons of Natural Language Processing (2020- present)
Generative AI (GEN AI) refers to a category of artificial intelligence systems designed to generate content, often in the form of text, images, or other media, that is contextually relevant and resembles content created by humans. Unlike traditional AI models that may follow pre-programmed rules or make predictions based on existing data, generative AI can produce original and diverse outputs.
One prominent example of generative AI is OpenAI’s GPT (Generative Pre-trained Transformer) series, including models like GPT-3. In late 2022, ChatGPT made headlines by attracting 1 million users within a week of its launch. By early November, the platform had amassed over 200 million monthly users, showcasing the significant impact of OpenAI’s innovations on the AI landscape.
This success story underscores OpenAI’s commitment to advancing NLP and its ability to deliver platforms that resonate with a vast user base. The influence extends beyond user metrics; it has played a pivotal role in the development of subsequent innovations like GPT-3, reinforcing OpenAI’s position as a trailblazer in conversational AI. Microsoft’sMSFT strategic investment further validates OpenAI’s crucial role in the evolution of AI and NLP, signifying industry-wide recognition of its contributions.
On November 6th, OpenAI introduced GPTs, custom iterations of ChatGPT, which amalgamate instructions, extended knowledge, and actionable insights. The launch of the assistants API facilitates the seamless integration of assistant experiences with individual applications. These advancements are viewed as foundational steps toward the realization of AI agents, with OpenAI committed to enhancing their capabilities over time. The introduction of the new GPT-4 turbo model brings forth improvements in function calling, knowledge incorporation, pricing adjustments, support for new modalities, and more. Additionally, OpenAI now provides a copyright shield for enterprise clients, exemplifying their ongoing commitment to innovation and client support in the evolving landscape of generative AI.
Built for safety: Anthropic (2021- present)
Anthropic is an AI safety startup founded in 2021 that leverages constitutional AI, an approach to train models to be helpful, harmless, and honest. The research team then developed CLAIRE, a large language model trained using the same constitutional basis. Anthropic’s’s research-driven approach and focus on AI safety place them at the forefront of developing responsible and beneficial AI systems as does the use of techniques like data filtering and controlled training environments to avoid biases or errors. Focused on common sense — the AI understands intuitive physics, psychology, and social norms, allowing it to give reasonable answers. Both Google and Amazon have invested in Anthropic.
Intel INTC and NVIDIA NVDA DIA: Powering the AI Revolution Through Hardware
Companies like Intel and NVIDIA have played a crucial and often underestimated role in the AI landscape by providing the hardware infrastructure that underpins remarkable advancements. Their development of powerful processors and graphics processing units (GPUs) optimized for machine learning tasks has been pivotal,facilitating not only the training but also the deployment of complex AI models, accelerating the pace of innovation in the field.
What’s Next? Responsible AI
Responsible AI refers to the design, development, and deployment of AI systems in an ethical and socially-aware manner. As AI becomes more powerful and ubiquitous, practitioners must consider the impacts these systems have on individuals and society. Responsible AI encompasses principles such as transparency, explainability, robustness, fairness, accountability, privacy, and human oversight.
Developing responsible AI systems requires proactive consideration of ethical issues during all stages of the AI lifecycle. Organizations should conduct impact assessments to identify potential risks and harms, particularly for marginalized groups. Teams should represent diverse perspectives when designing, building, and testing systems to reduce harmful bias which is why companies like Credo AI have jumped in to focus on a responsible framework.
Credo AI is an AI governance platform that streamlines responsible AI adoption by automating AI oversight, risk mitigation, and regulatory compliance. Their founder and CEO, Navrina Singh commented, “The next frontier for AI is responsible AI. We must remain steadfast in mitigating the risks associated with artificial intelligence.”
What’s Next? The Physical World
Spatial AI and robotic vision represent an evolution in how artificial intelligence systems perceive and interact with the physical world. By integrating spatial data like maps and floorplans with computer vision, itallows robots and drones to navigate and operate safely. Robotic vision systems can now identify objects, read text, and interpret scenes in 3D space, giving robots unprecedented awareness of their surroundings and the mobility to take on more complex real-world tasks.
New spatial capabilities are unlocking tremendous economic potential beyond the $17B already raised for AI vision startups. Warehouse automation, last-mile delivery, autonomous vehicles, and advanced manufacturing are all powered by spatial AI and computer vision, and over time they will offer more dynamic and versatile interactions with physical environments. This could enable revolutionary applications, from robot-assisted surgery to fully-autonomous transportation.
What’s Next? Customer-Centric AI Apps:
There is a shift happening right now in AI, from technology-centric solutions that solve infrastructure problems to customer-centric applications that solve our real-world human problems comprehensively.This evolution signals a move beyond the initial excitement of AI’s capabilities to a phase where technology meets the diverse and complex needs of end-users.
While the concept of a data flywheel remains relevant (reminder of the FlyWheel – more usage → more data → better model → more usage) , the sustainability of data moats is on shaky ground. The real moats, it seems, are in the customers themselves. Engagement depth, productivity benefits, and monetization strategies are emerging as more durable sources of competitive advantage.
Hassan Sawaf, CEO and Founder of AIXplain, highlights the power of a customer focused engagement approach. “We believe in AI agents that can help swiftly craft personalized solutions by leveraging cutting-edge technology from leading AI providers in real time. That’s what we’ve created with Bel Esprit and 40,000 state-of-the-art models with the capability to onboard hundreds of thousands more from platforms with proprietary sources in minutes. One click is all it takes for deployment, making Bel Esprit a game-changer in the AI landscape.”
Reflection
As we reflect on the success of what is now recognized as GEN AI, it is imperative to acknowledge the collective contributions of the tech titans that I’ve mentioned. Their advancements in deep learning, natural language processing, accessibility, and hardware infrastructure have not only shaped the trajectory of AI, but have also ushered in an era where intelligent technologies play an integral role in shaping our digital future.
Celebrating the pioneers in AI emphasizes their innovative spirit and unwavering commitment to advancing the boundaries of technology, paving the way for the sophisticated AI models that define our current era. A round of applause for the diligent technologists working at these companies.
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I’m COO at Unstoppable Domains, and Alumni of AWS and IBM. I’m also a chairwoman on the board of the nonprofit Girls in Tech, a former member of the Diversity Committee at the World Economic Forum, and currently a founding member of the Blockchain Friends Forever social movement for women in Web3. I hold and trade modest amounts of ETH and BTC. These days I’m passionate about enterprise use cases for decentralized technologies. My latest book “The Tiger and the Rabbit” is shipping on 8/30! It’s. Business Fable about AI, Web3 and the Metaverse!
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