A Brief History of AI and Why Your Business Should Care
Technologists have been creating innovative ways to offload intelligence into machines, however minor it may have been, since at least the Bronze Age. Until recently, no matter the complexity, traditional information technology (IT) machines have only been as intelligent as their programming. But new artificial intelligence models are different, and they’ve launched us into an economic revolution like we’ve never seen before and may not be expecting.
There are three primary reasons why:
- It’s easier than ever before to access the labor of machine intelligence.
- Machine Intelligence can now accomplish adaptive tasks without the need of specific handwritten programming for that task.
- These are thinking machines with emergent capabilities.
A brief history of AI
Since the first commercial computers in the 1950s, it has taken a skilled programmer to tell a machine what to do and exactly how to do it. The need for this specialized skill set has limited the power of computing to the people with the knowledge and talent to write code. The scope of what that code could accomplish has been limited to the time and money available to perfect its execution.
Historically, these limitations have placed the vast majority of computing power in the hands of companies who can hire the best software engineers and have the capital to fund large-scale and long-running software projects.
How AI changes the computing landscape
ChatGPT 3 captured everyone’s attention by putting a technology that understands and speaks natural language in front of the world. It was a scaled up and well trained application of the transformer model, a relatively new neural network model.
The interface is simple: talk to the machine and it talks back, almost like a person would. The machine understands what you’re saying and can intelligently respond with knowledge it’s acquired by learning all the text of the internet. Sounds simple, but it’s such a significant leap in technological capability we have yet to grasp its full potential.
ChatGPT reinforced that we are now living and working with machines that can expand their programming through observation, learning, and expert reinforcement of their output. As opposed to traditional computer software, it’s not necessary to reprogram AI for different images, languages, or tasks. It is general purpose, and through learning adaptable across domains. It is thinking machine intelligence.
Understanding and speaking language is a poignant example of this new capability. Language, especially natural language, does not follow logical rules and is impossible to accomplish with traditional computer programming techniques.
The logical rules of language are certainly not how we learn to speak or write. (Apologies to all my English teachers.)
For example, take the simple sentence, “The dog ran.” A toddler in an English speaking household knows the verb comes after the noun long before they know what a verb is. After hearing it enough times, they understand basic mappings of the language and its wildly random exceptions. “The small, smelly, brown dog” is not “The smelly, brown, small dog.” We know how to properly order adjectives even though we may struggle to articulate what it is or why.
Machine intelligence is now good enough to understand the complexities of language, images, video, movement, and more. Surprisingly, at this scale, these types of neural networks are even demonstrating emergent capabilities beyond anyone’s expectations.
Across industries, many existing machine intelligence tasks can now be offloaded to these generative models instead of to complex algorithms in traditional code. Tasks previously impossible to offload to machine intelligence are now fair game, impacting how we live our lives and do business — faster than we may realize.
What AI means for business
Today workloads that only need average intelligence are being offloaded to AI. Summarizing a contract, explaining legislation, creating meeting notes, writing simple code, and much more.
Knowledge work has been off limits to machine intelligence up to this point, but that’s no longer the case. It’s neither viable nor desirable to have people doing simple knowledge tasks that don’t require critical problem solving or creativity.
The economic impact of this technological shift is significant. According to a recent Goldman Sachs report, as much as two thirds of all occupations will eventually have tasks replaced with AI. Workloads such as legal and office administration can replace almost half of all the tasks today.
The use of AI is being applied to physical machines as well, creating robots which can accomplish adaptive physical tasks previously only possible by human labor. Driving a car, building a car, doing laundry, floating concrete, etc. — all become possible with the adaptability of scaled AI models and well built humanoid robots. While we may have had the physical hardware to accomplish these tasks, we’ve lacked the adaptability in machine intelligence to leverage it for mundane physical tasks.
That is changing quickly. BMW’s recent partnership with Figure AI, a humanoid robotics startup, validates that humanoid robot workers aren’t just the fever dream of Elon Musk with Tesla’s Optimus robot. There is real competition pushing these robots to be viable in a factory setting in the next year.
That’s clearly only the first step of their deployment. Musk envisions 10s of millions of Optimus robots at work and is creating the manufacturing capacity to back up that vision.
The future of AI
The nature of work is changing across all industries due to the impact of AI. Businesses need to consider how this technology will impact them and their employees — now — and ensure the technology is top of mind as it rapidly evolves.
Decades of what once seemed like sci-fi research is now commercially viable. Average human tasks are becoming increasingly feasible to accomplish with machine intelligence.
We all play a part in the evolution of this foundational technology as it shapes how we experience our lives and survive in the future. New ideas, new software and hardware products, and deep integration to existing products and business processes will be coming online over the coming decade.
The question we need to ask ourselves is this: Are we ready?
Originally posted by Shane Kempton via Linkedin.
Adapt to AI with Solutions from Phase 2
Our comprehensive strategies do more than leverage the creativity, potential, and innovation of AI; they incorporate the people, professionalism, and personal touch that matter to you, with elegant solutions that make sense and produce successful, sustainable outcomes.
Adapting to AI appropriately means embracing the right approach from the get-go. No matter where your business is in the adoption, implementation, or application of AI, the award-winning experts at Phase 2 can help develop and deploy AI tools that fit your unique needs. Contact us today to find out more about how we can integrate AI into your business.