Less than a year has passed since the release of many generative AI tools, and a significant number of companies have already adopted them in the workplace.
According to a new McKinsey survey assessing the impact of AI on companies, one-third of respondents said they were using generative AI tools to tackle at least one business function. Additionally, 40 percent of respondents said they would increase investments in AI due to advancements in generative AI.
The seemingly sudden arrival of generative AI caught many off guard, spurring lively discussions across the world — from kitchen tables to boardrooms — about its potential applications and consequences.
Meanwhile, others had been tracking its development before tools like ChatGPT or Midjourney captured the public’s attention.
For data scientists, who play an important role in the growth of data-driven technologies like AI and ML, these developments were anticipated. Still, those in the field have found unexpected applications for these new tools and continued to keep tabs on emerging technologies.
Data scientists at DISQO and Beyond Limits shared which technologies are impacting the field, and how they’re incorporating them into their projects and keeping tabs on emerging trends.
Beyond Limits blends high-level AI techniques with human-centric cognitive reasoning to help businesses optimize their workforces and overcome logistical challenges.
What are the emerging technologies that you see impacting data science right now or in the immediate future?
The hottest new tech is the generative AI models that are shaking up creative industries. The previous generation of AI technology was mainly classification and prediction for use cases ranging from advertising to equipment monitoring. Generative models, however, create new things with near human-like capability and quality. In 2023, we’ve seen the popularization of tools like ChatGPT for text, Midjourney for image and Gen-2 for video generation, bringing the power of AI into many new industries.
In 2023, we’ve seen the popularization of tools like ChatGPT for text, Midjourney for image and Gen-2 for video generation, bringing the power of AI into many new industries.”
These tools are still in their early days but this trend will accelerate with the quality of the generated content to improve to the point where they are real productivity game changers for everyone from designers to lawyers to data scientists.
How do you and your team members stay atop these technologies?
Being an industry leader means continually investing in exploring, learning and bringing new technologies in-house. First, we hire cutting-edge research leaders from top-notch universities to solve applied problems for the industry. Second, we actively partner with leading research institutions like Caltech to commercialize advanced algorithms and technology. Third, we challenge ourselves to continually develop new technology and raise the bar for others. Lastly, we proactively engage in community discussions, creating a two-way dialogue that demystifies AI for others so they see the potential and help us understand the people we work with and the problems they need to solve.
How have you incorporated any of these technologies into recent projects, or how do you plan to? How has that benefited your team?
We have been fast to adopt these new technologies in ways I didn’t see coming even six months ago. Using the GPT text models, we’ve created powerful tools to extract and structure meaningful information from unstructured data like documents that greatly reduce customer onboard costs and accelerate timelines. Another part of our team has been using tools to accelerate content creation like presentation slides and product white papers. As with all things, if you can’t beat ‘em join ‘em, and I’ve been excited to see how quickly and creatively the team has incorporated this new tech into what we do.
DISQO is an audience insights platform that tests and measures product and brand experiences and helps businesses make informed decisions for their customers.
What are the emerging technologies that you see impacting data science right now or in the immediate future?
AI, ML and natural language processing (NLP) are the emerging technologies having a major impact on data science in an attempt to bring a more personalized experience.
Personalization is becoming increasingly important as businesses strive to provide better customer experiences. By using data to understand individual preferences, businesses can create more relevant and engaging experiences more likely to lead to sales or other desired outcomes.
The combined use of these emerging technologies has the potential to revolutionize the way we work. For example, we now have ChatGPT and Bard — large language models being used to explore the intersection of NLP and AI. ChatGPT is a generative, pre-trained transformer model developed by OpenAI, and Bard is a similar model developed by Google AI.
The combined use of these emerging technologies has the potential to revolutionize the way we work.”
How do you and your team members stay atop these technologies?
Our team at DISQO stays up-to-date on trends and developments in the field of data science by reading industry publications and blogs, attending conferences and meetups, participating in our internal annual hackathon, taking online courses and experimenting with new technologies. We always encourage each other to share articles, blog posts and other resources. At DISQO, we believe in the importance of staying abreast of emerging technologies in order to be successful in the data science field. We also find it helpful to network with other data scientists and to learn from their experiences.
How have you incorporated any of these technologies into recent projects, or how do you plan to? How has that benefited your team?
I’ve incorporated ML into recent projects by using it to identify fraudulent activity in a variety of ways, such as identifying unusual spikes in user behavior, logins from different countries and patterns that are indicative of churn. This has helped to protect my team from financial loss and has increased customer retention.
We’ve also used ML to personalize user experiences by enhancing their redemption experience and recommending perks and content that are relevant to each user’s interests. This has helped to improve user engagement and satisfaction.
Finally, we’ve used it to automate tasks, such as monthly promotions and ad detection. It has freed up my team to focus on more strategic work.
