Plugins to be Added to ChatGPT, to Create a Platform

Announcement relates to previous message on Wolfram Plugins, but promises more yet.

OpenAI turns ChatGPT into a platform overnight with addition of plugins  in Venturebeat

Sharon Goldman@sharongoldman,     Michael Nuñez@MichaelFNunez    March 23, 2023 

OpenAI booth at NeurIPS 2019 in Vancouver, Canada

OpenAI today announced its support of new third-party plugins for ChatGPT, and it already has Twitter buzzing about the company’s potential platform play.

In a blog post, the company stated that the plugins are “tools designed specifically for language models with safety as a core principle, and help ChatGPT access up-to-date information, run computations, or use third-party services.”  ... 

A sign of OpenAI’s accelerating dominance

The announcement was quickly received by the public as a signal of OpenAI‘s ambitions to further its dominance by turning ChatGPT into a developer platform.

“OpenAI is seeing ChatGPT as a platform play,” tweeted Marco Mascorro, cofounder of Fellow AI.

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And @gregmushen tweeted: “I think the introduction of plugins to ChatGPT is a threat to the App Store. It creates a new platform with new monetization methods.”

In sharing the announcement, OpenAI CEO Sam Altman tweeted: “We are starting our rollout of ChatGPT plugins. you can install plugins to help with a wide variety of tasks. we are excited to see what developers create!”    ... ' 

Framework On the Power of Platforms

 Considerable embedded links to supporting information. 

A Framework for Understanding the Power of Platforms

By Irving Wladawsky by IWB / September 08, 2022 at 08:09AM .... 

This past July, MIT’s Initiative on the Digital Economy held its 10th annual Platform Strategy Summit. The hybrid Summit included a number of panels and keynotes throughout the day, a few of which I attended online. In particular, I’d like to discuss the very interesting presentation by Boston University professor Marshall Van Allstyne as part of a panel on emerging trends in which he raised and answered five fundamental questions about platforms:

Structure: Why do platforms have such high market caps but so few assets or employees?

Strategy: Why does traditional product strategy fail in platform markets?

Regulation: Why does traditional antitrust fail in platform markets?

Fake News: Why is misinformation such a hard problem?

Can Decentralized Autonomous Organizations dethrone platforms?

In his presentation, Van Alstyne, aimed to articulate a single framework that will help answer all five questions, that is, a consistent way of thinking about platforms based on the research that he and his colleagues have been conducting over the past decade. Let me summarize Van Alstyne’s presentation by first describing his unifying framework, followed by how the framework applies to each of the five key questions.

Platforms have long played a key role in the IT industry. IBM’s System 360 family of mainframes, announced in 1964, featured a common hardware architecture and operating system. The ecosystem of add-on hardware, software and services that developed around System 360 helped it become the premier platform for commercial computing over the next 25 years.

In the 1980s, the explosive growth of personal computers was largely driven by the emergence of the Wintel platform based on Microsoft’s operating systems and Intel’s microprocessors, which attracted a large ecosystem of hardware and software developers.  .... ' 

Platforms vs Users

 Obviously, but worth a thought:

Platforms Need to Work with Their Users – Not Against Them

by Ethan Bueno de Mesquita and Andrew Hall, May 04, 2022  in HBR.org

As online platforms have become dominant, many have leveraged their power by raising fees and changing rules. In the short run, this hurts the producers they work with — software developers, small retailers, game designers, content creators. In the long run,...more

As we write, thousands of online communities created for a wide variety of purposes — everything from providing crypto financial services to crowdsourcing art collecting — are building new democracies rapidly evolving systems for discussion, debate, voting, and representation. This movement, often known as Web3, has created an explosion of interest in giving ownership and decision-making power to community participants rather than to a small number of business executives.

This phenomenon highlights a critical challenge for traditional platforms like Amazon, Meta, Google’s play store, and Apple’s app store, gaming platforms like Roblox or Steam, and even for newer centralized crypto platforms like Coinbase and OpenSea. Historically, as platforms became dominant in their domain, they have raised fees and changed rules to their benefit and their producers’ loss. They could do so because those producers — be they software developers, small retailers, game designers, or content creators — had nowhere else to go. But once learned, twice a fool: How can platforms keep producers making new investments in building for environments whose undemocratic governance systems cannot credibly promise to reflect their interests in the long run?

There is a way. By granting governance tokens to producers that give them the unbreakable right to vote on key decisions about fees and rules, platforms can give producers the ownership and assurances they need to unleash their innovation — to the benefit of the platform, its users, and its creative partners.

We are academics who study democratic systems of governance, and we are also advisors in the tech sector who think about the future of decentralized governance. In this essay, we’ll explain the challenge platforms are facing in maximizing the efforts of their producers, we’ll show how insights from blockchain governance can help, and we’ll discuss some specifics of how to implement a governance-token system that avoids common pitfalls that democracies have been grappling with for thousands of years.

The Lock-in Problem

In the early days of Web 2.0 — the movement that gave us mega platforms like Amazon, Facebook, and Uber — producers flocked to build for new platforms because that’s where the users, and thus the profits, were. But as some platforms failed and others became dominant in their spaces, the producers’ outside options dwindled, and so did their market power.  ... ' 

L'Oreal Social Selling Platform

Some advances in Beauty care selling strategy.

L’Oreal Invests in Social Selling Platform as Part of E-Com Strategy

By CGT Staff  

As part of its acceleration strategy in e-commerce, L’Oreal announced a minority investment in US-American social selling platform Replika Software, Inc., made through its corporate venture capital fund BOLD Business Opportunities for L’Oreal Development.

As a turnkey social selling platform, Replika Software enables brands to activate at scale their network of social sellers to sell online, inspire on social media and connect with consumers anytime, anywhere. Founded in 2016 by Kareen Mallet, former fashion director at Neiman Marcus and Bergdorf Goodman, and Corey Gottlieb, advertising, marketing and tech entrepreneur, the company is based in New York and has offices in Paris.

“Social commerce is an exciting new form of e-commerce that enables consumers, influencers, experts, beauty or shop assistants to sell brands and products on social platforms through formats such as live shopping or livestreaming,” said Lubomira Rochet, chief digital officer of L’Oreal. “Today, e-commerce already represents 25% of L’Oreal’s revenues. The rise of social commerce is a great opportunity for our brands to reinvent the consumer beauty experience worldwide. We are very excited to partner with Replika Software, a pioneer in the field, to create social commerce at scale. Our ambition is to crack this new channel and create a healthy and dynamic ecosystem of social sellers for the beauty category.”... '

Platforms for Data Science

Good piece in O'Reilly about this question,  largely-non technical and useful thoughts. Passing it on ...

Why Best-of-Breed is a Better Choice than All-in-One Platforms for Data Science
All-in-one platforms built from open source software make it easy to perform certain workflows, but make it hard to explore and grow beyond those boundaries.

By Matthew Rocklin and Hugo Bowne-Anderson,  in O' Reilly 

Do you buy a solution from a big integration company like IBM, Cloudera, or Amazon?  Do you engage many small startups, each focused on one part of the problem?  A little of both?  We see trends shifting towards focused best-of-breed platforms. That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows.

This article, which examines this shift in more depth, is an opinionated result of countless conversations with data scientists about their needs in modern data science workflows.  ... " 

(Much more at the link)