The AI-Enabled Research Toolkit: Google Alerts, OpenAI and Similari

The AI-Enabled Research Toolkit: Google Alerts, Openai and Similari

In a sense, R&D professionals are spoilt for choice when it comes to automated search tools. There is now a wide (and growing) range of solutions that can streamline the process of monitoring technical data, and extracting insights from it. 

Here, we’re unpacking three solutions that augment human search capabilities: Google Alerts, ChatGPT3 and, of course, Similari, to find out where their strengths and weaknesses lie. 

Google Alerts: your trusty research sidekick for the last 20 years 

Google Alerts can be a powerful tool for gathering information about new and emerging trends, technologies, and ideas that impact innovation strategy. 

By simply signing in and setting some parameters, users can track industry keywords, flag key trends and stay up to date with the news in their field. They can even keep tabs on competitors, provided the information makes it into the news cycle (more on this later).

And it’s all served to them, daily, weekly, or however they prefer, via email. All in all, it’s a useful tool that can help innovators to at least keep up with the curve, even if staying ahead of it remains just out of reach, for reasons we’re about to explore. 

Everyone has a blindspot (even Google)

For all its (completely free) benefits, there are some limitations to keep in mind when it comes to using Google Alerts for innovation intelligence.

Available sources: vast, but limited in important ways

Sources are limited to pages indexed by Google, and within that, mostly news sources (recall what we said earlier about competitors). That may be enough for certain use cases, but it leaves a lot of relevant information out of the frame, especially when it comes to scientific and technical literature. 

Not everything worth knowing makes it into the news – and if it isn’t there, it won’t make it into a daily Google Alert.

The brute facts aren’t enough on their own

Users have noted long standing challenges like false positives (unrelated content that matches the keywords) or false negatives (relevant content that does not contain the exact keywords). 

Additionally, Google Alerts does not offer much customization, so users can’t combine multiple searches into a single alert. And because it’s email-only, there’s no easy way to combine all emails and news stories into a single source. Reporting on the facts, and analyzing their significance – that’s left up to researchers to do the old-fashioned way.

From data to insight: the missing step

Perhaps most importantly, Google Alerts can’t automate that crucial step from data to insight – and insights are what fuels innovation. The work of figuring out the story the data is telling remains with the user. In other words, it’s a valuable tool for exploration, but not exploitation.

ChatGPT3 and the future of AI-enabled research

Meanwhile, at this very moment, the internet’s favorite chatbot is having human-like conversations with millions of users. What are they talking about? In short, everything, including a wide range of business use cases: automating marketing & sales, debugging code, and most importantly for our purposes – R&D. 

But it’s not just the impressive NLP that has the whole world abuzz. It’s also the extraordinary ease of use that ChatGPT3 provides. The user simply gives an input, asks a question, and sits back while the generative AI works its magic. Unlike email-based alerts, this experience is conversational. The user can ask follow-up questions or demand justification. 

Scientists and researchers can curate their own corpus of technical information and feed it to the system, and leverage its computing power through that simple interface. 

ChatGPT’s limits are harder to find, but they exist

Since it appeared in 2022, ChatGPT has been used by millions of people, and it’s received intense scrutiny in the process. This has provided useful input for the platform itself, while pointing up its limitations. 

The problem of data (again): historical and reactive 

As we saw with Google Alerts, historical data can only take you so far. ChatGPT has limited visibility past 2021. And while that could change in the future, its text-based output is best suited to providing a historical account of past data.

Innovators seek uncommon knowledge, not the common ground

ChatGPT is adept at drawing on billions of data points to come to a single answer. It can tell users, usually with great accuracy, where the common ground lies in a specific scientific dispute. It can even point you to its sources (if you ask nicely). This is all extremely impressive. But it’s not what researchers need to help them innovate, because innovation is about challenging the status quo, and finding new ways to interpret the data. 

And even with a private corpus of texts to work with, ChatGPT’s output is always text-based. That’s ideal for marketing, or generating source code, but not for scientific research, where data visualization plays a vital role in decision making. 

Similari: insights at your fingertips

We would be remiss to not tackle the question of where Similari fits in this picture. In short, Similari allows researchers to go deep where other tools favor breadth. In a matter of minutes, researchers can configure Similari to start watching, learning and generating deep insights about their specific field of inquiry. 

Picking up where search analytics leaves off: an insight mechanism that learns over time

Traditional search analytics platforms excel at finding data and presenting it in a predefined way. But they leave the heavy lifting to the researcher or analyst who must spend time curating that information, deciding what is and isn’t relevant, and juggling multiple disparate data sources. Similari replaces that workflow with a unified, live feed of up-to-date insights.

And over time, Similari learns from the human user, absorbing their preferences and imitating their behaviors – all without explicit instruction, thanks to its sophisticated underlying ML framework. That’s how Similari is able to slash manual data monitoring time by 80% or more, while actually enhancing research outcomes and fuelling innovation. 

Harnessing the power of AI to know everything, all the time

Augmenting human capabilities with AI is now a priority shared by businesses in almost every industry. And as the market matures, it’s providing more and more targeted solutions for highly specified business needs. Similari is one of them. And, for innovation professionals at least, it’s one of the most effective. 

To learn more about how Similari enhances and streamlines research for R&D and innovation teams in the life sciences and beyond, schedule a demo with our team. We’re ready to show you everything you could be missing with traditional search analytics – and much more besides.

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