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It’s Time to Nurture Your Chatbot



Andrew Hong

In 1966 at the MIT Artificial Intelligence Laboratory, computer scientist Joseph Weizenbaum developed ELIZA, one of the first rudimentary chatbots. Created to simulate a conversation through basic pattern matching and substitution, ELIZA was able to follow scripts and directions in order to contextualize events. Eliza’s most famous script, DOCTOR, was able to interact with users through chat as if it were a psychiatrist.

ELIZA’s responses were so convincing that Weizenbaum reported that several users became emotionally attached to the program, occasionally forgetting that they were conversing with a computer.

Fifty Years After the ELIZA Chatbot

Over 50 years later, chatbots have become an integral part of everyday life. Chatbots can not only provide 24-hour-a-day customer service, but they can also facilitate purchases and even help brands with marketing and lead generation.

Yet even in 2022, we continue to see complaints that chatbots aren’t smart enough.

To say that a Chatbot is not intelligent enough is a wholly unfair assessment rooted in a misconception about what chatbots should be able to do.

Humans Expect Instant Bot Adults – but we Start With Bot Babies

The main problem is that consumers expect interacting with chatbots to be like pressing a magic button.

I like to think of chatbots as babies. But, of course, you wouldn’t expect a baby to be born and to then become a successful adult 18 years later without any input. So instead, a hands-on learning process is required to teach that child everything they need to know as an adult.

The Call Center Human

The same is even true in call centers — which are arguably the closest human parallel to chatbots — or at least the customer service version. Brands can’t simply hire new employees and expect them to be 100% effective customer service agents from day one.

Once again, a constant learning process comes as these reps field more questions from consumers and learn more about how the brand operates.

This same learning process is accurate for chatbots.

Growing Intelligence — Chatbots are Not One and Done

Just like children and new employees, you can’t expect bots to simply be intelligent and to be able to handle every task they confront. Yet many brands hit this roadblock after launching a bot: “It’s not smart enough! It’s not improving!”

Thankfully, the solution is simple: Data optimization or AI optimization for your bot.

No matter what they use bots for, brands with chatbots need to invest in conversational data tools so they can quickly analyze the data generated by customer interactions. A plan must be made about how to understand the bot and to help the bot improve. The gradual improvement will help the bot be able to eventually respond to and field a broader range of queries.

Nothing is Easy in Tech — and the Same Goes With Bots

Preparing and educating your bots is something that is perhaps easier said than done. Take, for example, a customer who wants to buy movie tickets through a bot. There are many different ways a customer can ask questions and approach the subject of buying movie tickets. Here are just a few options:

Tell me the movies this week.

What are the movies for this week?

What movies are playing this week?

What movies can I see this week?

What Other Questions Have You Asked When Searching for Tickets?

There are hundreds of ways users could ask questions for movie tickets or any other service that customers and clients contact a business for. However, in order to optimize the experience for clients and customers and make it an optimal customer experience — the bot will need some instructional “intellectual growth.”

And for this fictional movie bot to be “happy,” the brand would need examples of all the different ways (or at least additional ways) customers might ask this query — along with the appropriate response(s).

Manual vs. Automated

If your bot is updated manually, this process requires dozens of employees to pore through transcripts in Excel sheets and map responses. Again, this is potentially a huge waste of internal resources and a colossal waste of time for everyone.

Automated tools, however, can easily simplify this process and link training phrases, like, “What movies are playing this week?” with customer intent and will phrase an appropriate and pleasing response for your bot.

Don’t Miss the Boat With Bots

Brands that don’t optimize their chatbots miss out on a prime opportunity to increase ROI by reducing live agent costs while creating a channel that better serves their customers.

Nurturing your bot means that you’ll want to understand the importance of investing in tools that will continue to make your bot better. If you want a “smart kid” — you teach them. If you want a “smart bot” you teach them.

It’s that simple. Nurture your bot.

Image Credit: Kindel Media; Pexels; Thank you!

Andrew Hong

Andrew Hong is the CEO of Dashbot. Dashbot is a bot analytics platform that enables developers to increase engagement, acquisition, and retention through actionable data. Dashbot is backed by world-class investors including ff Venture Capital, Bessemer Venture Partners, Scrum Ventures and Samsung.


Fintech Kennek raises $12.5M seed round to digitize lending



Google eyed for $2 billion Anthropic deal after major Amazon play

London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs



Deanna Ritchie

As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations



Deanna Ritchie

As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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