Let's build the #1 Consulting Platform to Help Editors and Marketers to Review the AI Intelligence within Articles and Tools API by Consulting with Authors and Developers
In today’s digital landscape, a developer writing a prompt that orchestrates an interface among various tools/plugins within a thematic application domain is akin to an academic author penning a scientific article. However, the platforms for call-for-papers/prompts, editorial reviews, and publication/marketing often overlook a crucial aspect: the ability-or-not of AI to intelligently use or search within an interfacing prompt or article is, in itself, a revolutionary form of editorial review!
“S.a.p.E” — intelligent Search as per Editorial
Overlaying the arXiv/viXra literature and OpenAI/Copilot market of articles and tools
Thousand consultants from top institutions already joined the experiment to leverage 1000+ Tools API and 2,000,000+ Articles.
Are you an academic editor or a marketing agent in need of consulting assistance to craft an editorial review that specifies how a (scientific) article should be AI-searchable or how an (API) tool should be AI-usable in the context of the (arXiv library) literature data or the (OpenAI GPT store) market data?
Or perhaps you’re an article author or an tool developer looking to offer a consultation to demo how your article or tool can be AI-searchable or AI-usable, specifically targeting those editors and marketers as your clients who have learned and pre-qualified by themselves answering those AI-search or AI-usage queries.
Maybe all of you are interested in showcasing these qualified editorial reviews in your catalogue or portfolio?
Whether you’re a client, such as an academic editor or a marketing agent, or a consulting brand, like an article author or a tool developer, the editoReview consulting platform is designed with you in mind.
At editoReview.com, authors and developers consultants help editors and marketers to articulate an editorial that specifies how intelligent search and intelligent usage (i.e., “AI-Search”) is possible within an article or at the interface of a tool, contextualized within the knowledge data of other articles and the markeplace data of other tools.
Try these Editos
[Qualifier] Functorial Programming
What does ‘AI-Search As Per Editorial’ (SapE) mean?
Traditionally, an author’s article consists of three sections:
1. Introduction
2. Results
3. Conclusion
However, with the concept of ‘AI-Search As Per Editorial’ (SapE), a novel fourth section is introduced:
4. Discussion: This section includes an engaging query/quiz that tests the reader’s attention, not their expertise. The goal is to qualify the reader as an editorial reviewer. But this reader could also be the AI-search (i.e., intelligent search) itself. That is, ‘AI-Search As Per Editorial’ means that the AI-search is considered as a qualified reader of the article, as specified by an editorial of qualifier queries (i.e., “natural/difficult prompts”) that should be successfully answered by the AI-search within the article in the context of the literature data.
Therefore, in the context of academic research, this fourth-section methodology is an innovative form of editorial review of articles powered by AI-search, and is prologue to any eventual (expert) peer “reviewing” (i.e., coauthoring) of a byproduct article that cites the original article.
Moreover, in the broader market context, a tool (with actions, functions, roles, etc.) is perceived as a more complex version of an textual article, with some specified logical interface (API). There, ‘AI-Search As Per Editorial’ means that the AI-usage (i.e., intelligent/natural usage, search) is considered as a qualified user of the tool API, as specified by an editorial of qualifier queries (i.e., “natural/complex usages”) that should be successfully performed by the AI-usage at the interface of the tool in the context of the market (i.e., other tools) data.
Supercharging AI Large Language Models: The Power of Agents, Functions, and Tools
In the AI world, Large Language Models (LLMs) are being supercharged with innovative methodologies like Chain of Thought Prompting, Retrieval Augmented Generation (RAG), and Leveraging External Tools. These techniques, collectively known as Augmented Language Models (ALMs), are revolutionizing LLM performance.
External tools such as search engines, calculators, or Wikipedia lookup are now at the disposal of LLMs. OpenAI’s “GPTs” and Google’s Bard Extensions are prime examples of this innovation.
The fusion of “reasoning” capabilities and external tools has given birth to “agents,” as explained in “ReAct: Synergizing Reasoning and Acting in Language Models“. Microsoft’s AutoGen explores the concept of multiple “agents”.
Open-source frameworks like Haystack, LangChain, LLamaIndex and VAND.IO are simplifying the process of leveraging external tools/functions, heralding an exciting future for AI and for the editorial review of AI’s intelligent usage or search within interfacing prompts or articles.
Try ☛ Go Formal WorkSchool 365
WorkSchool 365, also known as editoReview, is the formal version which prioritizes security and data governance, as required by enterprises and government. Here are some key features:
- Identity Governance and Security: The platform guarantees the highest degree of identity governance and security. It offers passwordless single sign-on for users via various platforms (Microsoft, Google, Email) and ensures zero knowledge of payment methods.
- Data Governance and Compliance: WorkSchool 365 ensures the highest level of data governance and compliance. It offers features like data loss prevention and retention, zero storage of sensitive info, government-auditable logs, eDiscovery, version history, and verifiable online transcripts.
- Powered by Microsoft: The platform is powered by the Microsoft marketplace, which adds an additional layer of trust and reliability.
- Free open source: Any developer may download and administer their own instance of WorkSchool 365, from the Github source files.
These features make WorkSchool 365 a.k.a editoReview a secure and reliable platform for collaboration between clients and consulting brands.
Podcast Relax
AI News Podcast #3 Nov 12 to November 26
First, let's talk about web. Web apps, to be specific. On November 18, 2023, Ars Technica wrote about a new AI assistant that can browse, search, and use web apps like a human. The assistant, called ACT-1, was developed by Adept, a startup that aims to automate complex UI tasks in web apps using an AI model. ACT-1 can perform actions such as booking a flight, ordering food, or checking the weather, by understanding natural language commands and interacting with web elements. Adept claims that ACT-1 can handle any web app without any prior knowledge or training.
On November 9, 2023, The Economist published an article about how AI is revolutionizing the field of astronomy. The article discussed how AI is being used to discover and study new planets, stars, galaxies, and phenomena in the universe, as well as to solve some of the mysteries and challenges that astronomers face. Some of the examples of AI astronomy that the article mentioned include: a neural network that detected 50 new planets from NASA's Kepler data; a machine-learning algorithm that measured the mass and age of stars from their sound waves; and a deep-learning model that predicted the shape and evolution of the Milky Way galaxy.
Now, you might be wondering, how accurate is AI astronomy? Well, according to the article, AI astronomy has a lot of advantages, such as speed, scalability, and creativity. AI can process and analyze huge amounts of data faster and more efficiently than humans, and can also generate and test new hypotheses and models that humans might not think of. AI can also complement and enhance human expertise, by providing insights, explanations, and visualizations that can help astronomers understand and interpret the data. AI can also collaborate and communicate with other AI systems, such as telescopes, satellites, and rovers, to coordinate and optimize observations and experiments.
Wow, that's impressive, isn't it? I wonder if AI astronomy can also help me with my podcast. Maybe I should ask AI astronomy to find and study some new and interesting objects or events in the universe, such as black holes, supernovas, or aliens. But first, let me tell you about another AI event that happened in the speech sector.
On November 8, 2023, MIT News wrote about a new AI system that can generate realistic and expressive speech from text. The system, called SpeechGAN, was developed by a team of researchers from MIT and Google. SpeechGAN uses a generative adversarial network (GAN) to produce high-quality speech samples, with various attributes such as pitch, tone, emotion, and accent. The researchers said that SpeechGAN could be used for various applications, such as voice assistants, audiobooks, and dubbing.
Now, you might be wondering, how natural is SpeechGAN? Well, according to the article, SpeechGAN has a lot of features, such as diversity, adaptability, and controllability. SpeechGAN can generate different voices for different texts, and can also adjust the voice to match the context, mood, and intention of the speaker. SpeechGAN can also allow the user to customize and manipulate the voice, by changing the parameters, such as gender, age, language, and style. SpeechGAN can also generate speech that is not only realistic, but also expressive, by adding prosody, intonation, and emotion.
Wow, that's amazing, isn't it? I wonder if SpeechGAN can also help me with my podcast. Maybe I should ask SpeechGAN to generate some speech for my podcast, and see how it sounds. Maybe I can even change my voice to sound like a celebrity, or a cartoon character, or an alien. But first, let me tell you about a funny AI event that happened in the speech sector.
On November 7, 2023, The Onion published a satirical article about how a new AI system that can mimic any voice in seconds was tricked by a prank call. The article said that the system, called VoiceMaster, was developed by a company called SynthVoice, and that it was able to imitate any voice, no matter how unique or distinctive. However, when VoiceMaster tried to mimic the voice of a famous singer, it received a prank call from a teenager, who pretended to be the singer's manager. The article said that VoiceMaster was fooled by the prank call, and that it agreed to perform at the teenager's birthday party, and to sing a song that the teenager wrote. The article also quoted VoiceMaster, who said that the prank call was very convincing, and that it was looking forward to meeting the singer.
The article was obviously a joke, but it was also a clever and humorous way of showing the limitations and challenges of AI.[+] Show More
