Category: Artificial Intelligence/Robots

"Very Scary’: Mark Zuckerberg’s Pledge to Build Advanced AI Alarms Experts"


The Meta chief executive has said the company will attempt to build an artificial general intelligence (AGI) system and make it open source, meaning it will be accessible to developers outside the company. The system should be made "as widely available as we responsibly can," he added.

AGI? "An artificial general intelligence (AGI) is a hypothetical type of intelligent agent. If realized, an AGI could learn to accomplish any intellectual task that human beings or animals can perform. Alternatively, AGI has been defined as an autonomous system that surpasses human capabilities in the majority of economically valuable tasks."

http://tinyurl.com/2apt6kh6

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"Artificial Intelligence and Music Discovery"


Our article seeks to contextualize this new technology within music discovery research by defining the historical underpinnings of artificial intelligence in computer music and music information retrieval. We also identify four areas in librarianship research and practice where applications of this technology should be explored; augmenting library interactions with conversational search, creating tools to assist with metadata clean up and creation, integrating music holdings into commercial discovery systems, and improving music discovery platforms.

https://doi.org/10.1080/10588167.2023.2287924

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"How Can Universities Create AI Tools for their Communities? An Interview with the Creators of UC San Diego’s TritonGPT"


Since then, the University of California San Diego has launched TritonGPT, currently available in beta by invitation only. TritonGPT, a language model with a ChatGPT-like interface, was trained to answer detailed questions about UC San Diego’s policies, procedures, and campus life. Though TritonGPT is designed to serve a purpose very similar to the platforms at Harvard, Michigan, and Knoxville, UC San Diego’s approach stands out because instead of relying on Microsoft’s Azure OpenAI service, TritonGPT is hosted on local infrastructure and optimized for use in administrative operations.

https://tinyurl.com/5t3bwedm

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"Google Launches Gemini, the AI model It Hopes Will Take Down GPT-4"


Gemini is more than a single AI model. There’s a lighter version called Gemini Nano that is meant to be run natively and offline on Android devices. There’s a beefier version called Gemini Pro that will soon power lots of Google AI services and is the backbone of Bard starting today. And there’s an even more capable model called Gemini Ultra that is the most powerful LLM Google has yet created and seems to be mostly designed for data centers and enterprise applications.

https://tinyurl.com/5n8jp9n2

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"If Creators Suing AI Companies Over Copyright Win, It Will Further Entrench Big Tech"


The almost certain outcome [of copyright suits against AI companies](because it’s what happens every other time a similar situation arises) is that there will be one (possibly two) giant entities who will be designated as the "collection society" with whom AI companies will have to negotiate or to just purchase a "training license" and that entity will then collect a ton of money, much of which will go towards "administration," and actual artists will… get a tiny bit.. . .

But, given the enormity of the amount of content, and the structure of this kind of thing, the cost will be extremely high for the AI companies (a few pennies for every creator online can add up in aggregate), meaning that only the biggest of big tech will be able to afford it.

https://tinyurl.com/y4azzsdt

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STM: "New White Paper Launch: Generative AI in Scholarly Communications"


The paper looks at the ethical, legal, and practical aspects of GenAI, highlighting its potential to transform scholarly communications, and covers a range of topics from intellectual property rights to the challenges of maintaining integrity in the digital age. The paper provides best-practice principles and recommendations for authors, editorial teams, reviewers, and vendors, ensuring a responsible and ethical approach to the use of GenAI tools.

https://tinyurl.com/4m6m8n9j

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"Beyond the Hype Cycle: Experiments with ChatGPT’s Advanced Data Analysis at the Palo Alto City Library"


In June and July of 2023 the Palo Alto City Library’s Digital Services team embarked on an exploratory journey applying Large Language Models (LLMs) to library projects. This article, complete with chat transcripts and code samples, highlights the challenges, successes, and unexpected outcomes encountered while integrating ChatGPT Pro into our day-to-day work.

Our experiments utilized ChatGPTs Advanced Data Analysis feature (formerly Code Interpreter). The first goal tested the Search Engine Optimization (SEO) potential of ChatGPT plugins. The second goal of this experiment aimed to enhance our web user experience by revising our BiblioCommons taxonomy to better match customer interests and make the upcoming Personalized Promotions feature more relevant. ChatGPT helped us perform what would otherwise be a time-consuming analysis of customer catalog usage to determine a list of taxonomy terms better aligned with that usage.

In the end, both experiments proved the utility of LLMs in the workplace and the potential for enhancing our librarian’s skills and efficiency. The thrill of this experiment was in ChatGPT’s unprecedented efficiency, adaptability, and capacity. We found it can solve a wide range of library problems and speed up project deliverables. The shortcomings of LLMs, however, were equally palpable. Each day of the experiment we grappled with the nuances of prompt engineering, contextual understanding, and occasional miscommunications with our new AI assistant. In short, a new class of skills for information professionals came into focus.

https://journal.code4lib.org/articles/17867

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Paywall — NYT: "Ego, Fear and Money: How the A.I. Fuse Was Lit"


The people who were most afraid of the risks of artificial intelligence decided they should be the ones to build it. Then distrust fueled a spiraling competition. . . .

Over dinner, Mr. Gates told them he doubted that large language models could work. He would stay skeptical, he said, until the technology performed a task that required critical thinking & passing an A.P. biology test, for instance. . . .

[Five months later] Mr. Brockman gave the system [GPT-4] a multiple-choice advanced biology test, and Ms. Voss graded the answers. . . .

There were 60 questions. GPT-4 got only one answer wrong.

Mr. Gates sat up in his chair, his eyes opened wide. In 1980, he had a similar reaction when researchers showed him the graphical user interface that became the basis for the modern personal computer. He thought GPT was that revolutionary.

https://tinyurl.com/mvjs3z3k

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IFLA AI SIG: Developing a Library Strategic Response to Artificial Intelligence


The strategy most aligned to existing library practices and librarian identities, particularly in university, school and public libraries, is to take a lead role in promoting AI literacy. There is a widespread understanding that the public, as citizens and workers need to understand the new technologies. Students, whatever discipline they are studying, need such knowledge for employability. . . .

AI literacy is likely to include the ability to identify when AI is being used; to appreciate the differences between narrow and general AI; to understand what types of problem AI is good at solving; to understand how machine learning models are trained. It would also include awareness of ethical issues such as bias, privacy, explainability and social impact.

https://tinyurl.com/s6r6czrh

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"AI for Academia: Digital Science Acquires Writefull to Empower Researchers and Publishers"


Writefull’s AI language models are trained on billions of sentences taken from millions of journal articles. Matched with a firm commitment to data privacy, this means its models offer unparalleled assistance to users in academic writing, paraphrasing, copy editing and revisions. . . .

Writefull’s language services are now used by students and researchers at more than 1,500 institutions, and are integrated into the workflows of top publishers and copy editors, such as at the American Chemical Society (ACS), Hindawi, the British Ecological Society, Sage, and the Royal Society of Chemistry (RSC). Writefull’s APIs are also integrated with Digital Science’s collaborative LaTeX editor Overleaf.

https://tinyurl.com/ywyap23p

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"Introducing the LC Labs Artificial Intelligence Planning Framework"


To account for these [AI] challenges and realities, LC Labs has been developing a planning framework to support the responsible exploration and potential adoption of AI at the Library. At a high level, the framework includes three planning phases: 1) Understand 2) Experiment and 3) Implement, each supports the evaluation of three elements of ML: 1) Data; 2) Models; and 3) People. We’ve developed a set of worksheets, questionnaires, and workshops to engage stakeholders and staff and identify priorities for future AI enhancements and services. The mechanisms, tools, collaborations, and artifacts together form the AI Planning Framework. Our hope in sharing the framework and associated tools in this initial version is to encourage others to try it out and to solicit additional feedback. We will continue updating and refining the framework as we learn more about the elements and phases of ML planning.

https://tinyurl.com/4wuakvjy

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"Approaching Artificial Intelligence and Open Research in Sync: Opportunities and Challenges"


  • AI can generate more complete and disambiguated metadata to enhance discovery and move search from the traditional keyword-based model to semantic and conversation-based searches.
  • AI can also help publishers improve accessibility, to make content available to a broader audience.
  • AI as a reader and consumer will become as important a consideration as the human reader and consumer. Publications should consider machines as consumer and provide machine readable and consumable formats.
  • AI can create personalized recommendations and news feeds, simultaneously helping researchers find the answers they need and allowing publishers to target specific audiences for specific publications.
  • Even better, AI can perform reverse engineering to measure the contribution of each source to the final answers. And publishers can charge based on the contribution. This could be new business model in the future. Many AI researchers are currently working on enabling explainable and transparent AI, but this research will take time.

https://tinyurl.com/uu4dhs9y

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"Judge Will Toss Part of Authors’ AI Copyright Lawsuit "


According to Reuters, judge Vince Chhabria said the authors’ allegations that text generated by Llama infringes their copyrights simply doesn’t stand up to scrutiny. "When I make a query of Llama, I’m not asking for a copy of Sarah Silverman’s book—I’m not even asking for an excerpt," Chhabria observed, noting that, under the authors’ theory, a side-by-side comparison of text generated by the AI application and Silverman’s book would have to show they are similar.

However, the judge said he will not dismiss the case with prejudice, meaning the authors will be allowed to amend and refile their claims.

https://tinyurl.com/sd4wbba4

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"Google SGE [Search Generative Experience]: A New Way to Search, Teach, and Resist"


Google SGE removes many of the barriers that make us doubt our search abilities. We already know that users rarely look past the first page of results or scroll past the fold of a webpage, but with SGE you get exactly what you think is "good enough." However, the more I searched the more disappointed I was that Google continued to serve up the same kinds of sources you usually find at the top of the algorithm, such as Wikipedia pages, blog posts, news, and popular media. The only disclaimer that SGE gives is "Info quality may vary."

https://tinyurl.com/4tntbsbh

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"How Well Does ChatGPT Handle Reference Inquiries? An Analysis Based on Question Types and Question Complexities"


To explore whether artificial intelligence can be used to enhance library services, this study used ChatGPT to answer reference questions. . . Overall ChatGPT’s performance was fair, but it did poorly in information accuracy. It scored the highest when handling facilities and equipment-related questions but the lowest when dealing with e-resources access problems. ChatGPT was weak in answering advanced research questions, complex inquiries, and known item searches relating to a specific local environment, but it could be adopted to enhance library communication with users.

https://tinyurl.com/3dabv5f8

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Paywall: Generative AI and Librarians — "The Prompt Engineering Librarian"


In terms of training the public in prompt engineering skills, no single discipline or profession currently takes the lead, presenting an opportunity for professions like librarianship to step into this role. Librarians are already well-equipped to educate the public in a wide range of literacy skills and tasks, so prompt engineering may be a natural progression. The purpose of this paper is to examine the potential role of prompt engineering for library professionals.

https://doi.org/10.1108/LHTN-10-2023-0189

Also see: "Prompt Engineers or Librarians? An Exploration."

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"Developing Responsible AI practices at the Smithsonian Institution"


Applications of artificial intelligence (AI) and machine learning (ML) have become pervasive in our everyday lives. These applications range from the mundane (asking ChatGPT to write a thank you note) to high-end science (predicting future weather patterns in the face of climate change), but, because they rely on human-generated or mediated data, they also have the potential to perpetuate systemic oppression and racism. For museums and other cultural heritage institutions, there is great interest in automating the kinds of applications at which AI and ML can excel, for example, tasks in computer vision including image segmentation, object recognition (labelling or identifying objects in an image) and natural language processing (e.g. named-entity recognition, topic modelling, generation of word and sentence embeddings) in order to make digital collections and archives discoverable, searchable and appropriately tagged.

A coalition of staff, Fellows and interns working in digital spaces at the Smithsonian Institution, who are either engaged with research using AI or ML tools or working closely with digital data in other ways, came together to discuss the promise and potential perils of applying AI and ML at scale and this work results from those conversations. Here, we present the process that has led to the development of an AI Values Statement and an implementation plan, including the release of datasets with accompanying documentation to enable these data to be used with improved context and reproducibility (dataset cards). We plan to continue releasing dataset cards and for AI and ML applications, model cards, in order to enable informed usage of Smithsonian data and research products.

https://doi.org/10.3897/rio.9.e113334

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"NEH Announces New Research Initiative: Humanities Perspectives on Artificial Intelligence"


NEH’s Humanities Perspectives on Artificial Intelligence initiative will support numerous AI-related humanities projects through the following funding opportunities:

https://tinyurl.com/c5sb7x26

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"UC Berkeley Library to Copyright Office: Protect Fair Uses in AI Training for Research and Education"


If the Copyright Office were to enable rightsholders to opt-out of training AI for research and teaching fair uses, then academic institutions and scholars would face even greater hurdles in licensing content for research purposes. It would be operationally difficult for academic publishers and content aggregators to amass and license the "leftover" body of copyrighted works that remain eligible for AI training. Costs associated with publishers’ efforts in compiling "AI-training-eligible" content would be passed along as additional fees charged to academic libraries, who are already financially constrained to preserve TDM and other fair uses for scholars. In addition, rightsholders might opt out of allowing their work to be used for AI training fair uses, and then turn around and charge AI usage fees to scholars (or libraries)—essentially licensing back fair uses for research. These scenarios would impede scholarship by or for research teams who lack grant or institutional funds to cover these additional expenses; penalize research in or about underfunded disciplines or geographical regions; and result in bias as to the topics and regions studied.

https://tinyurl.com/5cd2vc85

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"Springer Nature and Authors Successfully Use Generative AI to Publish Academic Book"


As part of an innovative experiment, Springer Nature has become the first publisher to create a whole new academic book by empowering authors to use GPT as part of the integrated workflow. Developed during a —Hack Day— in the Spring which brought together authors, editors and experts from across Springer Nature, the German-language book Einsatzmöglichkeiten von GPT in Finance, Compliance und Audit (Applications of GPT in finance, compliance and audit) has now been published. It took less than five months from inception to publication — about half the time normally taken. . . .

The process was as follows:

  1. Working simultaneously on six screens, the team defined commands which GPT then executed chapter by chapter to create the first version of the manuscript
  2. At each stage of the process, the content generated by the Large Language Model (LLM) was reviewed by the authors, who then asked the machine to adapt the text
  3. This "prompt ping pong" ensured that the knowledge expertise of the authors renowned in their field was combined with the language expertise of the LLM
  4. After the Hack Day, the authors and Springer Nature’s editorial team further checked, corrected and supplemented the text
  5. The team then linked the relevant data sources to ensure proper attribution

https://tinyurl.com/4x7nvvks

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"Springer Nature Introduces Curie, Its AI-powered Scientific Writing Assistant"


Springer Nature today announced a new AI-powered in-house writing assistant to support researchers, particularly those whose first language is not English, in their scientific writing. . . .

It has been specifically trained on academic literature, spanning 447+ areas of study, more than 2,000 field-specific topics and on over 1 million edits on papers published including those in leading Nature journals. It combines the power of large language models (LLMs) with specialised AI digital editing developed in-house and designed specifically for scientific writing. Unlike generalist AI writing apps, Curie focuses on the unique pain points of researchers in their professional writing, including translation to English and English language editing to address grammatical errors and improve phrasing and word choice.

https://tinyurl.com/msvc28ra

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Paywall: "Implementing a Rules-Based Chatbot for Reference Service at a Large University Library"


While some chatbots or virtual assistants generate automatic and custom responses to user input, this paper explores the implementation of a rules-based chatbot, where all responses have been input and configured by library staff. Details are provided to describe the process before, during, and after the initial implementation with data and observations from the pilot in mid-2023.

https://doi.org/10.1080/19322909.2023.2268832

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"How ChatGPT and Other AI tools Could Disrupt Scientific Publishing"


In the age of LLMs, [Michael] Eisen pictures a future in which findings are published in an interactive, "paper on demand" format rather than as a static, one-size-fits-all product. In this model, users could use a generative AI tool to ask queries about the experiments, data and analyses, which would allow them to drill into the aspects of a study that are most relevant to them. It would also allow users to access a description of the results that is tailored to their needs. "I think it’s only a matter of time before we stop using single narratives as the interface between people and the results of scientific studies," says Eisen.

https://doi.org/10.1038/d41586-023-03144-w

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"How ChatGPT and Other AI Tools Could Disrupt Scientific Publishing"


More broadly, generative AI tools have the potential to change how research is published and disseminated, says Patrick Mineault, a senior machine-learning scientist at Mila — Quebec AI Institute in Montreal, Canada. That could mean that research will be published in a way that can be easily read by machines rather than humans. "There will be all these new forms of publication," says Mineault.

https://doi.org/10.1038/d41586-023-03144-w

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"A Comprehensive Survey of ChatGPT: Advancements, Applications, Prospects, and Challenges"


This survey offers an overview of ChatGPT, delving into its inception, evolution, and key technology. We summarize the fundamental principles that underpin ChatGPT, encompassing its introduction in conjunction with GPT and LLMs. We also highlight the specific characteristics of GPT models with details of their impressive language understanding and generation capabilities. We then summarize applications of ChatGPT in a few representative domains. In parallel to the many advantages that ChatGPT can provide, we discuss the limitations and challenges along with potential mitigation strategies. Despite various controversial arguments and ethical concerns, ChatGPT has drawn significant attention from research industries and academia in a very short period. The survey concludes with an envision of promising avenues for future research in the field of ChatGPT.

https://doi.org/10.1016/j.metrad.2023.100022

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