There is a mediocre content deluge coming to the internet the likes of which we have not seen. What if you could produce 10x the amount of content at at 10x cost savings, what would you do? Even if the content were mediocre would you still be tempted to take advantage of the ability to throw content against the well and see what sticks?
What would that mean for websites, link farms, private blog networks, link builders, SEOs and search engine algorithms? What would it mean for quality, believable, original content?
What is GPT-3 & How Does it Work?
GPT-3 stands for Generative Pre-trained Transfomer. Per Wikipedia:
GPT-3 is an autoregressive language model that uses deep learning to produce human-like text. It is the third-generation language prediction model in the GPT-n series (and the successor to GPT-2) created by OpenAI.
As a natural language processor and generator, GPT-3 is a language learning engine that crawls existing content and code to learn patters, recognizes syntax and can produce unique outputs based on prompts, questions and other inputs.
But GPT-3 is more than just for use by content marketers as witness by the recent OpenAI partnership with Github for creating code using a tool dubbed “Copilot.” The ability to use autoregressive language modeling doesn’t just apply to human language, but also various types of code. The outputs are currently limited, but its future potential use could be vast and impacting.
How GPT-3 is Currently Kept at Bay
With current beta access to the OpenAI API, we developed our own tool on top of the API. The current application and submission process with OpenAI is stringent. Once an application has been developed before it can be released to the public for use in any commercial application, OpenAI requires a detailed submission and use case for approval by the OpenAI team. Among the requirements for approval are limitations on the types and lengths of outputs allowed to be pulled from the API.
For instance, the company currently prohibits OpenAI’s use on certain social platforms, including Twitter with the believe that massive tweets produced at scale could be used for nefarious or political ends and sway or create public opinion that may not be accurate.
Additionally, OpenAI further restricts any tool using the API from an output greater than 200 characters. With a mission to serve a much higher purpose than producing more mediocre content that humans are likely to never read.
Keeping tight controls on a beta product that could be used nefariously is more than smart, but it doesn’t mean would-be abusers won’t still find a way to circumvent the rules.
Examples of GPT-3 Content at Scale
Since we developed our own tool on the OpenAI platform, we have used it extensively in-house, testing it on some of our own and client projects. Here are a few examples where we have found it extremely helpful in creating content that would otherwise cost more and take more resources to implement:
- Landing pages at large scale. While the tool is not so talented at creating blog-type content, it is actually fairly astute at its ability to create landing pages for things like “locations” and “industries” served. We recently tested this by creating over 1,100 city and state landing pages for internal project at BIKE.co where we trained several offshore assistants on the tool and instructed them on how to plug GPT-3 prompt outputs into a basic replicated Elementor design on WordPress.
- Podcasts introductions. We have found introductions to podcasts–for ourselves and for clients– can more easily be produced using GPT-3. To make it even creepier, we have even tested AI-powered voice technology for the audio of the podcasts themselves. Imagine that, a entire podcast show where no humans create any of the content!
- Social media. While there are some current restrictions on the length and type of format where GPT-3 can be used, there is a true possibility
- Email spamming. Spam algorithms currently catch patterns in emails, particularly as it relates to copy. That is one way AI/ML are being used to filter garbage emails, but if not policed a large amount of unique emails could be sent separately with a lower likelihood of getting flagged for spam.
- Content spinning. Because the API can produce longer, unique outputs with a simple, shorter input, the ability to spin and recreate similar content for use in online publication is a real temptation, even if you do have to stitch it together to make it happen.
These only represent a small potential of the uses (legitimate and otherwise) for GPT-3. While we are only currently scratching the surface of the potential of how this particular AI tool will impact us, there are those whose motivations, while not negative per se, will still use the tool to create a deluge of content that adds little to no value other than simply providing online content for content’s sake.
Why Content at Scale Will Ruin the Current State of the Internet
20 years ago we joked that you had to be careful what truths you believed that had been pulled from the web. New technology actually may revert us back to a bygone era when facts are looser and content quality is worse, not better. In fact, it is estimated that 7.5 million new blog posts are created each day. Imagine if machines could do it in the cloud with only a simple algorithm?
Content will similar to how Syndrome on Disney’s “The Incredibles” described his plan for a post-superhero world where he would provide machines that would make everyone super:
When everyone is super, no one will be.
That’s exactly what is happening with GPT-3’s ability to provide content at massive scale.
When anyone can create content at scale with little to no cost, then the only thing that will differentiation in the future will be the quality. In short, I agree with OpenAI’s sentiment that strict controls should be placed on the quantity and purpose of the content produced by GPT-3. Otherwise, we would have much more of much less when it comes to written content on the web.
Fintech Kennek raises $12.5M seed round to digitize lending
London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.
According to an Oct. 10 tech.eu 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 Kennek.io; Thank you!
Fortune 500’s race for generative AI breakthroughs
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!
UK seizes web3 opportunity simplifying crypto regulations
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!