Shaping the Future: AI's Impact on Industries in 2024

AI is changing the world one day at a time while we, humans, are still in the pilot seat. But what if AI takes the pilot seat? Can we foresee it? Can we outsmart it? Where is the line, and are we close to crossing it? We stand at a pivotal moment in the era of AI, where the decisions we make in our businesses and as a society now will have an immense influence over the forthcoming future.

Looking at the state of AI, we can safely say that It has the power to change the course of the world and our lives. As the founder of Pixyle.ai - a startup utilizing computer vision AI to automate manual data entry processes, I find myself at the forefront of this stimulating wave of change. I am excited to share how we can embrace AI, the challenges and promises it holds, and what businesses need to consider as we embark on this transformative journey.?

The Short Timeline of AI: from Perceptron to Transformers?

Let’s take a step back and look at AI's timeline:

1950s-1960s: The Birth of AI and the Perceptron

In 1950, Alan Turing proposed the Turing test in "Computing Machinery and Intelligence," asserting that "machines can think." Frank Rosenblatt's 1957 creation of the first perceptron laid the foundation for early artificial neural networks. These ideas became instrumental in the evolution of advanced deep learning models seen today.

The 1980s-1990s: Post-AI Winter and the First Neural Networks

After the "AI winter," the 1980s and 1990s marked an AI resurgence. The 1980s introduced Lisp machines, expert systems, and the connection machine, with the mid-1980s bringing neural networks and behavior-based robotics. Marvin Minsky's "The Society of Mind" and the 1990s highlighted AI milestones, Geoffrey Hinton and Yann LeCun introduced neural network advancements, and IBM's Deep Blue won in chess. Besides all these advancements, limited computational power hindered widespread adoption during this era.

Late 1990s-2000s: Machine Learning Emerges

In the late 1990s and early 2000s, machine learning took center stage, employing statistical methods for data-driven decision-making and emphasizing practical applications with a focus on shallow learning. Notable highlights from the 2000s include the introduction of interactive robot pets, Cynthia Breazeal's contributions to sociable machines, Honda's humanoid robot ASIMO showcasing human-like walking, and the successful resolution of Checkers by University of Alberta researchers.

The 2010s: Deep Learning Dominance and the Birth of the Transformer

In the 2010s, deep learning took the spotlight, marked by breakthroughs in image and speech recognition using neural networks. The pivotal moment in 2012, led by Alex Krizhevsky's ImageNet results, propelled the shift from shallow to deep learning across the AI field. In 2017, Google introduced the transformer model, and in 2018, the Transformer architecture emerged, giving rise to influential models like OpenAI's GPT-2 in 2019.

The 2020s: Advances in Generative AI

In the 2020s, generative AI has made big strides with influential models like DALL-E, Stable Diffusion, and Midjourney, expanding the creative and adaptive capabilities of artificial intelligence. Also, Microsoft releases Turing Natural Language Generation (T-NLG), a 17-billion-parameter model. AlphaFold 2 by DeepMind wins the CASP competition for protein structure prediction. OpenAI introduced GPT-3 in May 2020, followed by GPT-4 in March 2023 via a chat interface. This is the moment when the whole world witnessed the huge advancements in AI and realized how powerful it can become.

2023:? What’s happening now?

On Nov 6th, 2023, OpenAI made significant strides at their Developer Day , introducing an AI marketplace for custom GPTs. Everyone can now build tailor-made GPTs and chatbots for specific tasks and use cases. ChatGPT is now also multimodal, it can see, hear, and speak. On another front, Elon Musk’s advancements in AI chips are becoming a reality. Neuralink got approval from the US FDA for its first human tests.

The Current Landscape of AI in Various Industries

In the fast-moving field of AI, exciting progress has been happening across all industries. We're now in a moment where AI isn't just a sidekick but is evolving toward learning on its own from vast amounts of data, without constant supervision and the need for labeled data. This change is really important when we look at where AI is headed and how it could shake up different industries.?

AI in E-commerce

AI is transforming e-commerce. It’s making the online shopping experience engaging and tailored to each customer's needs and preferences. On the other hand, AI is also helping e-commerce businesses and teams be more efficient in their work. Pixyle's AI, for example, simplifies the process of adding products to online stores by efficiently creating detailed tags, titles, and descriptions from images. Adobe Firefly makes product image editing super easy for photo production teams. Google Shopping uses Generative AI to easily add different backgrounds to product images. Zalando released AI Style Agents for consumers to talk to and suggest items based on individual tastes and asks. Algolia's vector search improves search accuracy by considering the meaning behind words, providing more relevant results. Together, these companies showcase how AI is revolutionizing e-commerce.

But what’s next? I am confident that, at one point,? AI will not only help with product data creation and image moderation but will also be generating complete e-commerce stores and product pages on its own. Something like this is already happening in the web development world. Builder.ai for example, uses generative AI to build apps from scratch in mere minutes.

AI in Arts and Marketing

When it comes to the industry where people are most afraid that AI will replace them, it is probably the arts, creativity, and marketing niche. The idea of AI quickly coming up with and running entire marketing campaigns in just 15 minutes is unsettling for marketers. However, Coca-Cola's "Masterpiece" and Nutella's "Nutella Unica" campaigns show a collaborative approach where AI can create positive changes, providing more and better opportunities for creative jobs.

AI in Entertainment

Spotify's breakthrough in automatically translating languages in podcasts using voice hints at the broader use of AI in instant voice translations. This innovation could impact traditional translation jobs, as AI accomplishes tasks in seconds that currently take humans a day. Meanwhile, Meta's Emu Video and Emu Edit aim to enhance creative expression and communication, turning text into videos and enabling precise image editing. Generative AI is also transforming Hollywood , as seen in the film "Everything Everywhere All at Once," powered by Runway AI. However, challenges like unauthorized data use require attention for responsible AI use, striking a balance between innovation and ethical standards in the dynamic landscape of generative AI.

AI as Your New Employees to Hire

How about this? Artisan introduces fully AI digital workers , employees like Ava and Noah, who seamlessly integrate with human teams. These AI workers automate tasks, optimize workflows, and self-improve daily. With an intuitive dashboard for easy management and the ability to chat for tasks, updates, or advice, they represent a transformative shift in work efficiency. This innovation highlights AI's evolving impact on work, providing dynamic and collaborative solutions that redefine traditional employment concepts.

AI in Medicine?

Probably, one of the most noble uses of AI is to be found in medicine. AI is making big strides in changing how we diagnose illnesses. In a UK study on breast cancer, using AI to read mammograms reduced the chances of getting things wrong by 5.7% for false positives and 9.4% for false negatives. In South Korea, another study found that AI was better at spotting breast cancer, especially in finding lumps (90% accuracy compared to 78% for radiologists) and catching early-stage cancer (91% accuracy compared to 74% for radiologists). Just think of how many lives could be saved if diagnoses are established in the early stages of disease development.

The Learnings

All of the examples above show how AI advancements can have ripple effects across various professions. But, what we need to understand is that AI won’t replace people doing their jobs - it will replace people who don’t use AI to do their jobs. AI is here to help us and it is up to us to take advantage of its power. The benefits are limitless.?

As AI rapidly takes over various industries, the key factor shaping its impact is the data it relies on. What we feed into AI models determines their learning and, consequently, what unfolds in the real world. This crucial concept has the potential to make or break businesses and has prompted the establishment of new rules and regulations to steer AI's course.?

New AI Rules and Regulations

As AI progresses, there's a shift from human-guided control to independent exploration. However, concerns arise, highlighted by an alarming incident where AI generated plans for 10,000 chemical weapons in just six hours . That is why the need for responsible AI development has been recognized, and global rules are now in place. In the U.S., President Biden's Executive Order sets new standards for AI safety, privacy, equity, and innovation. Similarly, the EU's AI Act categorizes systems by risk, prohibiting high-risk AI and requiring transparency for generative AI. It's a shared challenge to balance technological progress with ethics.

How Should Businesses Leverage AI in 2024?

AI is exploding - no doubt about that. Traditionally, machines learned from human-provided data, but now they're gaining the ability to learn on their own—a game-changing moment in the AI industry.

And, as we're on the brink of a revolution in the AI industry, businesses need to take charge and get ready for what's coming. Here are some suggestions:

1. Sense of Urgency: Businesses should recognize the need for swift AI adoption. Companies that embrace AI early on gain a competitive edge, becoming more agile and efficient. Boards of directors should develop strategic plans, empowering teams to explore AI applications for daily operations, drive innovation, and influence process improvements.

2. Prioritize Ongoing Learning: Given the fast-paced nature of AI development, businesses should invest in continuous learning programs and AI awareness. This ensures the workforce stays adept at leveraging evolving AI technologies, adapting to new challenges, and maximizing the benefits of personalized AI solutions.

3. Invest in Responsible AI Practices: Businesses should approach AI development with a strong commitment to ethical practices. Everybody needs to understand the potential risks of unsupervised learning, learning from past instances like biased models (as seen in Amazon's hiring algorithm ). We should implement safeguards to prevent unintended outcomes, ensuring fairness and inclusivity in AI applications.

Embrace the Future Now:

Start Integrating AI into Your Operations for Optimal Efficiency

In conclusion, the fusion of AI with the global industry showcases the tremendous impact technology can have on our world. Moving ahead, businesses need to step into the AI revolution with a mindful approach, being cautious and responsible. The future is AI, and by journeying down this road alongside technology, we can craft a world where innovation, responsibility, and progress thrive together in unison.

Looking forward, I'm currently writing an article on specific applications of AI in e-commerce, so stay tuned for more insights directly from the core of the AI world.