Last week marked the 1 year anniversary of the launch of ChatGPT. The launch took the world by storm and took AI mainstream, reaching a user base of 180m in only a year, the fastest ever adoption of a new technology, with 100m reportedly using it weekly.
ChatGPT wowed people worldwide by enabling human-like conversations with a computer. It is a type of Generative AI (Gen-AI) that can produce various forms of content in seconds, including text and imagery, based on the prompts it’s given.
ChatGPT helped evolve the average person’s impression of AI, from the existential threat to humanity as portrayed on movie screens, to a tool that empowers everyday humans on the screens they use daily.
For many it changed AI from something mainly conceptual (beyond interacting with frustrating customer-service chatbots), to a practical experience readily available on personal devices to answer any question and accelerate knowledge work globally.
In reality large language models (LLMs) like ChatGPT don’t really understand what we ask them, they are simply pattern matching to provide the highest probability response, and as such are not truly intelligent. While ChatGPT represented a step-increase in the impact of AI, it’s still regarded as Artificial Narrow Intelligence (ANI), meaning it performs the narrow task it was created for effectively but the tasks it can perform are limited.
The next evolution of this, Artificial General Intelligence (AGI), is when AI behaves in human-like ways across all tasks. “The singularity” is a term referring to this moment when artificial intelligence surpasses human intelligence, but despite recent advances, this is still a way off. However at the rate investment is now flowing into the AI space, it may come faster than experts once predicted.
Beyond its narrow task focus, other Gen-AI limitations include presenting false information as facts (known as hallucinations), potential biases in data it’s trained on, and privacy concerns with any prompt-data entered.
Despite these limitations, Gen-AI’s usefulness cannot be denied. It can accelerate our research, organize our thinking and rewrite our wording at a rapid speed. Used smartly it can be a catalyst for creativity that makes us more effective and efficient in our individual jobs.
Top companies are now leveraging Gen-AI not only to drive impact at the individual level, but across entire teams and departments, to achieve step gains in productivity across the entire organization.
Bangkok-based Appsynth is one such company. Appsynth is one of the region’s largest digital consultancies, helping enterprises design, develop and grow flagship consumer applications and launch new digital businesses. Appsynth was ranked as Thailand’s #1 fastest growing IT company in Financial Times’ 2023 High-Growth Companies index.
As a thought leader in digital and the practical use of new technologies, Appsynth was quick to apply the powers of Gen-AI across its entire business. It formed a Gen-AI Committee with representatives from every function, tasked with identifying Gen-AIs most impactful use cases and the best tools to accomplish these. Appsynth is now streamlining its activities across all departments, as follows:
Accelerating iterations, generating product ideas, crafting personalized user experiences, predicting design trends, and enhancing collaboration.
Fast investigation of previously unfamiliar technologies to fulfill broader requirements and increased efficiency through streamlined test writing and code suggestions, using GitHub Copilot, to avoid repetitive writing.
3. Quality Assurance
Rapidly generating test cases and helping non-developer QAs generate code for automated testing.
4. Tech Leadership
Research and Proof of Concept (POC) development to solve problems, generating sample code, optimizing code performance and creating technical documentation based on proposed solutions.
5. Project Management
Initial document formation, making sense of complex information by summarizing documents, and smoothing out the process of project planning and tracking, and preparing visually impactful slides without design support.
6. Product Management and Growth
Rapid landscape analysis to identify reference applications for further analysis, and identifying optimization opportunities for our client’s products.
Crafting communications, grammar checks, and general knowledge research and offloading repetitive tasks and time-consuming desk research.
Drafting emails more efficiently, assisting in recording income, expenses, and processing numerical results in accounting, and helping with the translation of various documents.
“In today’s competitive digital landscape, accelerating time-to-market for new initiatives is essential, to stay ahead of competitors and start learning from real customer usage as quickly as possible”, said Bob Gallagher, Appsynth’s Founder and CEO.
“Using Gen-AI we have cut down the time of numerous tasks, enabling us to get clients to market faster than their competitors who aren’t realising the full potential of such technologies.”
While Gen-AI is accelerating the software development process, it is hard to estimate the exact impact it will have on a given project in advance. However with a commitment to utilise the technology wherever feasible, it enables more to be achieved with the same resources. For Appsynth’s clients with dedicated teams working on a time and materials basis, this means the value Appsynth is able to deliver for the same time and cost is now greater.
In addition to designing and developing complex consumer applications for its customers, Appsynth also provides consulting services to help clients enhance processes and enable new capabilities inside their own teams. So beyond using Gen-AI technology to accelerate its core digital development services, Appsynth will begin helping clients adopt Gen-AI best practices to achieve similar efficiencies across their own organisations, implementing the technology securely and compliantly to meet the needs of today’s modern enterprise.