Binny Gill has a diverse and extensive work experience spanning multiple roles and companies. Binny is currently the Founder and CEO of Kognitos, a company focused on making programming accessible and enabling businesses to optimize their operations and customer experiences.
Binny’s a prolific inventor in computer science, with close to 100 patents, and believes that more people need to be able to instruct computers in natural language.
Could you share the genesis story behind Kognitos?
During the pandemic, my son decided to make the game of tic-tac-toe in Python. He built it in a couple of days, and I was a proud dad. However, I woke up the next day realizing that I had made the same game in about the same amount of time 30 years ago. I was the same age then. It dawned on me that programming has not become any easier over the decades. All that we have done is made more humans understand programming.
I went back to challenge my son to write another program. This time to find out if a number is prime or not. I found myself trying to teach programming by saying that he needed to “think like a machine”. That didn’t go anywhere. Then I realized what I was missing. I taught him to first write “the pseudo code” (just an explanation of what the program will do but in his own words). That was easy, it took 5 minutes. We started converting that into working code. It was hard for a first-time programmer and after a few hours my son said he didn’t want to code any more.
I was taken aback. Why was programming so hard even after 7 decades of innovation and thousands of programming languages being invented? I offered my son that I will find a language that works for him. He immediately said, “why can’t this work?” — he was pointing to the pseudo code he had written in 5 minutes for the prime number problem. I laughed and said, “No, those are just your notes. The machine can’t understand that”.
“Why can’t it be like Alexa?”, he said incredulously. And that was a light bulb moment. After a long silence I told my son to not learn Python. Kognitos was born.
Can you dive into the inner workings of the platform? How is Kognitos catering to customers?
Kognitos is the world’s first automation platform built entirely in English. We have built a first of a kind interpreter for natural language that understands and executes natural language code. The impact of this is huge as now all business users, whether highly technical developers, or financial analysts, or high-school graduates processing invoices all can understand and use the same automation tool.
From the business perspective, the impact occurs in several areas. The time required to build automation is reduced as there is no necessary translation from English steps to python or other coding languages. The business user is now able to use their specific functional knowledge to handle exceptions and teach Kognitos how to handle future examples. This lessens the burden on IT. And lastly, compliance and IT are happy as all of the data on what both humans and AI did is stored in English, so it’s easily accessible as needed.
What are some of the machine learning algorithms that are used, and what part of the process is Generative AI?
Kognitos combines two fundamental technologies to deliver an automation platform that works in the manner of people. Just like humans have two sides of their brain, one that is highly logical, and one that uses pattern recognition and intuition to be creative, Kognitos has two sides. First, Kognitos is built on our patented interpreter, the world’s first to “Run English as code”. The interpreter (the logical side) provides the consistency, determinism and auditability needed for operating business processes.
We combine this with LLMs (the creative side), to enhance its capabilities and make the platform even more approachable for users. One example of this is with our conversational exception handling. When an error occurs (for example a document is missing in a workflow), Kognitos feeds the error to an LLM and instructs it to present the error in a way that the business user can understand it and respond. The user can then respond in English (like a conversation) telling Kognitos how to solve the problem. We use the best model for each situation including GPT 3.5, GPT 4, Palm 2, and others. As the business user handles exceptions, the system is learning from these examples and using a few prompting techniques can quickly understand what the business user does without the need for extensive training, as used to be case with traditional AI models.
How does Kognitos differentiate itself from competition? How is it used at the enterprise level?
Kognitos differentiates itself by removing the need for highly trained developers or data scientists, and in doing so eliminating much of the maintenance cost in automation. RPA developers are not only expensive but also in short supply. This results in competitive products (which are primarily built on early 2000s technology), long backlogs of unfinished projects in IT, software on the shelf, and high maintenance costs for what is already implemented.
Because Kognitos democratizes automation by making it accessible to everyone in the language of business, English, now business users are able to be involved in the automation process. Organizations may still want more technical users to build the automations as a part of their governance process, but the handling of exceptions shifts to the business users who have the subject matter knowledge to handle them. This greatly reduces the costs of all automations, creating strong ROI cases for automations that previously were not viable with RPA. As a result, businesses primarily use Kognitos for processes that are high-volume, repetitive, manual, and contain lots of exceptions or variations. Commonly these processes are found in Finance, Accounting, HR and supply chain.
How did your background in cloud software influence your vision for Kognitos? What are the areas of overlap between cloud and generative AI?
My vision is to bring computer literacy to the masses – not by forcing more humans to speak the language of the machines, but by upskilling machines to speak the language of humans. All my life I have spent learning myriad computer languages and have always felt that the experience of programming has been suboptimal. Why can’t the machine ask me a simple question instead of crashing in the middle of a long automated process? I believe that the paradigm of programming (be it cloud or be it process automation or AI) is fundamentally shifting today to natural language.
Ever since we moved from punch cards and assembly programming to C, Fortran and Cobol, there has not been any fundamental improvement in programming languages until now. We are now moving from the realm of precise languages for programming computers to imprecise languages for programming then using natural languages. The reason why this is becoming possible now is because machines are finally able to talk back to the human to clarify the intent of the program. That is huge and will impact all of computer science (not just cloud but every piece of software around us). I believe all business apps will now be written in English.
How does Kognitos prioritize human oversight while leveraging rapid advancements in AI?
In the industrial age, we built machines much more powerful than us and relieved people of manual labor. The key element to making it safe was that we humans had the “steering wheel” in our hand to control the machine. With the rapid advancements of AI, we are now entering the era when we will be building machines much more powerful than us which will relieve us of mental labor. However, where is our new “steering wheel”?
At Kognitos, we believe that steering wheel is the democratization of automation review. While we harness the creativity of LLMs to write automations, making it possible for all humans to review those automations is the key to remaining safe and in control. By providing a platform where what the machine plans to run deterministically is expressed in natural language, Kognitos is giving most of humanity that much needed “steering wheel”.
Just like the human brain, the Kognitos interpreter is dualistic in nature (Logic + LLM). Logic is the antidote for hallucinations, and by building the LLM layer on top of the logical interpreter, Kognitos is able to enforce validations in a deterministic manner after any LLM-based step that requires review. Further, being a stateful system, the Kognitos platform records every action of both the human and AI in English and thus is a 100% auditable and whitebox AI system.
At the moment, most business activities are done via computers and mobile devices. What needs to change before businesses truly embrace new technologies like augmented reality and virtual reality?
As we enter the era where machines pass the Turing Test, all the traditional interfaces that were invented because machines could not understand humans directly will get dismantled. Already I prefer not to open apps on my smartphone if Alexa or Siri can do the job for me. Human-Computer Interface design will give way to Human-Human Interfaces for machines. So, I foresee all drag-and-drop and menu-based interfaces giving way to natural language-based interfaces.
To answer the question as to whether augmented and virtual reality will be embraced by businesses – we first need to see that happen in the consumer world. If it isn’t happening in our kitchens at home, then it is unlikely to happen on any large scale in businesses. What I foresee is a revolution in robotics following the revolution in Generative AI. Those robots will be the interface to machines both at home and in businesses. Humans like to keep things real.
What do you expect to be the next big breakthrough in AI?
The invention of artificial general intelligence (AGI) that could learn to accomplish any intellectual task that human beings can perform might happen, but as a society we should discourage that. I favor the invention of a collection of ANI (Artificial Narrow Intelligence) models that will help humanity in narrow tasks. However, by combining these ANI models via a logical and auditable system we can achieve monumental tasks while still being in control of the overall process.
What is your vision for future advancements in business process automation?
The role of humans in businesses is going to dramatically change. First business process information that in people’s heads will get translated into machine code using natural language platforms like Kognitos. Once the processes are in the machine, by running those processes, the machine will start to build a business journal of everything that happens in the business. That creates a treasure-trove of data that really captures the essence of any business.
Eventually, superhuman narrow intelligence models will run each aspect of a business (from marketing to sales to engineering). That “talent” will never leave the business anymore. Humans will have a review only – almost legislative role. The humans will approve new policies and decide on ethical questions and take responsibility for business actions. However, most of the operations of the business will be done by machines.
Is there anything else that you would like to share about Kognitos?
At Kognitos we deeply care about the future safety of humanity in the presence of super-human intelligence. The collective power of humans today is expressed through the machines we have built. Those machines, be it factories or cars or war machines, are controlled by computers. Today Generative AI is writing programs to control these machines. And those programs are expressed in traditional computer languages, and it is hard to convince ourselves that there won’t be any biases or hallucinations creeping into those generated programs. The only way to keep ourselves safe is to review all those programs. However, reviewing traditional programming languages requires developers and we don’t have enough of them in the world.
We are currently living in the dark ages of computer literacy, with 1 in 200 people able to review any code. By changing the language of automation to English, Kognitos will allow 100x automations to be reviewed by humans, amplifying the review bandwidth of humans by orders of magnitude and keep humans safer in the presence of super-human AI.
Thank you for the great interview, readers who wish to learn more should visit Kognitos.