Robert Weissgraeber is the Managing Director and CTO of AX Semantics, where he heads up product development and engineering. Robert is an in-demand speaker and an author on topics including agile software development and Natural Language Generation (NLG) technologies and a member of the Forbes Technology Council. He was previously Chief Product Officer at aexea and studied Chemistry at the Johannes Gutenberg University and did a research stint at Cornell University.
What initially attracted you to the space of Natural Language Generation (NLG)?
Writing and the way it has traditionally been executed, has not seen significant innovation since the advent of the typewriter 200 years ago and the word processor in the late 1960s. Three things attracted me to the NLG sector. First, witnessing the challenges and hardships people face and continuously endure with having to create vast quantities of content and text. For example, there are literally people who work in e-commerce that have to write hundreds of similar, yet unique t-shirt and clothing descriptions every month as new products come in. The amount of people needed to do this is astronomical, time-consuming, costly and impossible to scale. I knew the ability to utilize AI to automate content generation (vs. trying to produce content manually) would be a game changer for many industries who must regularly create mass volumes of content — not only in English but also many other languages.
Second, seeing the type of ‘low tech’ solutions others brought to the market — like spinning tools or poorly implemented NLG tools with ‘Enterprise UX’ — only solidified my attraction to the power of NLG.
Lastly, I wanted to work on something that wasn’t a rendition of the next online shop or the next “Uber for X”, but something capable of solving a really hard tech problem while also creating a solution for a real-world challenge. A perfect NLG solution with the ability to redefine content generation for the digital age can reduce ‘noise’ for all humanity, since it allows for super-precise communication.
Could you discuss some of the NLG solutions that are offered by AX Semantics?
AX Semantics is a 100% SaaS-based NLG solution with an easy to use UI (user interface). Customers build their own content generation machine by configuring their business application with our NLG tool, which automates content in 110 languages in a matter of minutes — including cross-data generation such as Chinese text from English data. As a result, companies can take data and information and create unique content rapidly and at scale regardless of perpetual business and cultural shifts.
There are a myriad of use cases for NLG technology. Different industries use it to solve content challenges unique to their sectors:
- E-commerce: Most customers use our NLG software to generate large volumes of unique product descriptions (critical for SEO), category content or personalized emails like basket dropout recovery emails.
- Brand/Customer Communications, including Social Media: Brands and content agencies use NLG to keep a steady flow of fresh blog content, or to create and populate unique social content across multiple social media channels — and can do so in 110 languages.
- Media or ‘Robot Journalism’: Publishers use our NLG software for election reporting or data-based journalism such as pollution-level monitoring, stock table earnings, sports scores and crime blotters — freeing up journalists to work on more creative, engaging journalism or hard-hitting investigative stories. In many ways, content generation software is helping to revive local journalism, particularly for cash strapped small newspapers. Journalism has been in a tight spot since 2000 as newspapers have cut reporters and editors or shut down entirely. NLG is actually an unlikely ally in the push to save journalism.
- Financial Services/Banking: Financial analysts, brokers, and executives face the demand to quickly update the content required by state and federal laws and regulations, such as details about investment plans, risk assessments, and financial filings — all of which must be updated regularly. Our NLG solution addresses the pain point of recurring financial reports, regulatory filings, executive summaries, and other written communication – all of which typically require massive amounts of financial data from disparate sources to be gathered, analyzed and translated into text customized for a broad range of audiences and languages. Banking and finance employees can effortlessly turn mountains of data into real-time actionable written narratives, create reports, descriptions of terms and loans, draft regulatory filings, and documents detailing investments — in more than 110 languages — all with minimal training — freeing up bandwidth for higher-value activities and responsibilities.
- Pharmaceutical: Pharma companies use our HIPAA-compliant NLG software to generate regulatory Clinical Study Reports (CSRs) on medications up to 40% faster, by automating 30% of writing the CSR. This is crucial because the most challenging phase of bringing a drug to market is the human drug trial, or Phase III, during which time, clinicians must write a CSR that describes the pharmacological impacts and trial outcomes. Typically, data collected from the human drug trials is gathered and medical writing teams manually compile the report, however, this outdated, onerous and time-consuming process can potentially delay life-saving medications from coming to market sooner and cost pharmaceutical companies millions. A capacity challenge also exists. Writing a CSR report typically takes several months to complete, which limits the number of CSRs a team of medical writers can produce annually.
A writer’s voice is considered important in journalism and other types of writing, can you discuss the importance of drafting “personalities” for content generated by NLG?
With ‘data-to-text’ solutions like our NLG pipeline approach (in contrast to text-to-text, corpus-based stuff like GPT- 2/3), the writer is an essential and critical part of the creative process. The writer configures a lot of meaning levels between the data and adds ‘micro-templates’ for all aspects of the text, which allows the machine to select and combine all aspects in a ‘bag of words’ approach.
Can you discuss what hybrid content generation is and how employees can take advantage of this?
Hybrid content generation is where human and machine work together. Each actor focuses on the aspect they do best. Humans prioritize the creative part, writing style and specific content selection, including curation and definitions. The machine takes care of production, grammatical correctness building and scaling the content.
Hybrid content born from a partnership between man and machine fills a pressing need for fresh, vital content around the clock. Our software generates content that is almost indistinguishable from a human writer. Employees can use content generation to create new content that can be changed and updated at a moment’s notice. Working with content generation software allows them to not only fulfill, but exceed their job requirements and expectations.
With content being able to be created on the fly how will content quality be quantified?
Ultimately, it will be measured and quantified based on results. Early on, we had discussions about measuring quality aspects that were subjective to personal meaning, i.e. “I like this phrase or that,” etc., but this can now be measured objectively since scaled A/B testing is now possible. One of our customers, for example, struggled between the decision to use formal or informal languages (some non-English languages have that codified), and were able to test this out to see what worked best.
Can you share your opinions on how content will become decentralized?
No one source or market has a monopoly on content generation or the ability to scale content anymore. That’s the power of NLG technology and software — it delivers equal opportunity and equal access to companies large and small.
With access to valid data sources from all over the world along with NLG and publishing technology, businesses of all sizes can build scaled content, and adapt it to their own needs while using NLG technology to keep it continuously updated. For example, a customer service department can produce their own product descriptions with a focus on service-specific content, or an online marketer can tailor their content to be sales oriented — all without added maintenance or cost.
What are going to be some of the new “unlocked” business opportunities from this type of content generation?
First of all, we’re going to see totally new types of hyper-personalized content where lots of data sources are combined to produce content for a specific individual, such as a weather report that accounts for someone’s travel itinerary or financial services with individualized fund reporting. Second, as companies increasingly embrace the digital age, they’ll be able to utilize automated content generation to create a more robust online presence for their business.
Could you discuss some of the potential aspects for social good from NLG?
Consumers are inundated with a continuous stream of communication — texts, emails, countless ads and promotions — across multiple channels, including their mobile devices, computers and even the mail, they need to scroll through and read to find the information they want and need.
NLG allows for individualized, precise and noise-reduced communication. Imagine receiving only newsletters or reports that take your personal information into account and adapt it to your needs. NLG provides a better, more thoughtful way to reach customers in a way that matters to them.
What are some enterprises that are currently using AX Semantics?
Approximately three years ago after validating our solution with select clients, we began to introduce our NLG solution to the mass market. We had hundreds of customers try our software and build their individualized solution with AX Semantics. We then fine-tuned the necessary learning materials and onboarding process. A lot of those initially small customers now have scaled their content needs with us, including companies like Deloitte, Adidas, Nestlé, Otto and Beiersdorf.
Is there anything else that you would like to share about AX Semantics?
We’re very proud of the fact AX Semantics received recognition as one of the world’s top five providers of natural language generation platforms by Gartner, and that we were named a top emerging company in the NLG market by Forrester.
Lastly, in addition to our own client base and sales, we’re looking for companies that want to build their own vertical use cases on top of our technology, and we are actively supporting those companies with training, etc. So if you are building a new product or company and want to use content generation we’d love to speak with you.
Thank you for the great interview and the detailed answers regarding NLG, readers who wish to learn more should visit AX Semantics,
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