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Monday, November 06, 2023

Fear and Loathing In AI

There is a strong tendency to sensationalize the potentially catastrophic consequences of artificial intelligence, which has become prevalent in public perception. The fear and exaggeration surrounding AI technology have primarily been caused by inaccurate media portrayals that often overlook the nuanced realities of this field. Despite the remarkable advancements in machine learning and other areas of AI, there are still many limitations and challenges that must be overcome before AI can achieve its full potential and take over the world.

It is important to approach this technology with a balanced perspective, acknowledging its potential benefits and the potential risks that must be addressed.

In the ongoing conversation about the impact of AI on society, librarians can provide valuable contributions by leveraging their expertise in countering misinformation and promoting critical thinking. 

Throughout history, librarianship has played a crucial role in shaping debates by providing access to accurate information and resources and by advocating for the importance of critical inquiry and analysis. As AI technology continues to evolve and shape our world, librarians have an opportunity to engage with the broader community and encourage thoughtful reflection on the ethical and social implications of these advancements.

This essay will delve into AI apocalyptic sensationalism, which refers to the fear and loathing surrounding the potential dangers of artificial intelligence. To gain a better understanding of this phenomenon, the historical precedents for librarianship's influence on debates related to emerging technologies are examined. 

Understanding AI Apocalyptic Sensationalism

AI apocalyptic sensationalism is a phenomenon in which individuals and media outlets tend to amplify and overstate the potential hazards and capabilities of artificial intelligence technology. 

This tendency can result in the creation of an atmosphere of fear and panic, leading to a distorted perception of the actual risks involved. It is important to approach discussions about AI technology with a balanced and evidence-based perspective to avoid unnecessary alarmism and to facilitate a constructive dialogue about the opportunities and challenges of this rapidly evolving field.

The concept of intelligent machines surpassing human intelligence or even revolting against humans has been a recurring theme in science-fiction literature and movies for decades. 

The idea of a bleak and dystopian future where machines dominate and humans are subjugated has been explored in various ways by different authors and filmmakers. From classic works like the Terminator franchise to more recent films like Ex-Machina and Her, the portrayal of sentient machines has captivated audiences for years and fueled debates about the potential risks and benefits of artificial intelligence.

The reasons behind this exaggerated portrayal stem from both genuine concerns about unforeseen consequences of advancing technology and sensationalist tendencies within media outlets seeking attention-grabbing headlines.

In today's world, it is crucial to recognize the impact of media portrayals on public perception. The ease and speed of information dissemination through social media platforms make it all the more necessary to consider. 

The spread of misinformation through these channels can create a distorted understanding of various issues among citizens needing essential knowledge or expertise. 

Consequently, public discourse often tends towards alarmist narratives that rely on sensationalism rather than informed discussions based on scientific evidence and critical analysis. As we navigate through such a complex and dynamic information landscape, we must remain vigilant and cautious in our consumption and sharing of information.

Examining Precedents for Librarianship's Influence on Debates

Throughout history, librarians have played an instrumental role in shaping and guiding debates by actively countering misinformation and promoting critical thinking. They have traditionally served as reliable gatekeepers of information, diligently working to ensure that individuals can access accurate and trustworthy resources while simultaneously discouraging the proliferation of biased or inaccurate materials. By performing this crucial function, librarians have been instrumental in fostering a culture of intellectual curiosity and debate while also helping to ensure that our collective understanding of the world remains grounded in facts and evidence.

Librarians have also been at the forefront of defending critical thinking and intellectual freedom. One of the most significant instances was during the McCarthy era when librarians played a vital role in resisting censorship attempts and ensuring that people had access to a wide range of viewpoints. They stood up against the government's attempts to suppress ideas and maintain control over information.

Similarly, during the HIV/AIDS crisis, librarians played a crucial role in providing accurate information about the disease while countering harmful myths and stigma. They curated collections that provided people with the most up-to-date research and resources on the virus, helping to dispel misinformation and educate the public. Their efforts played a significant part in reducing the stigma around HIV/AIDS and increasing public understanding of the disease.

Overall, librarians' advocacy for critical thinking and intellectual freedom has been admirable and impactful, and their work has helped to promote a more informed and open society.

The Potential Role of Librarianship in Shaping the AI Debate

As AI technology continues to advance and impact our society, librarians can play a crucial role in facilitating informed discussions about its benefits, drawbacks, and ethical implications. With their expertise in organizing, evaluating, and disseminating information, librarians possess valuable skills in information literacy that enable them to identify and assess reliable sources of information, filter out misinformation and biased content, and present complex topics in ways accessible to the general public. 

By curating collections of resources on AI, including books, articles, and online databases, librarians can help bridge the gap between technical experts and laypeople, providing a better understanding of the technology's capabilities, limitations, and potential impact on society. This can foster a more informed and engaged public discourse about AI and its role in shaping our future.

In this context, librarians hold a unique position as neutral facilitators who can foster dialogue among stakeholders. They possess a wealth of knowledge regarding diverse perspectives, which allows them to provide balanced information and encourage critical engagement with complex technological topics. By leveraging their expertise, librarians can play a pivotal role in breaking down complex AI concepts and making them more accessible to a wider audience. Furthermore, they can help individuals navigate the ethical and social implications of AI, ensuring that the technology is developed and deployed responsibly and sustainably.

Strategies for Librarians to Shape the AI Debate

To influence conversations around AI technology, librarians can adopt several practical steps:

Librarians can be vital in promoting ethical considerations, transparency, and accountability within AI development processes. 

They can provide valuable insights by highlighting potential risks associated with algorithmic biases or privacy infringements, which can help developers make informed decisions. By staying up-to-date on the latest developments in AI technology and the associated ethical concerns, librarians can guide developers on responsible practices. 

With their expertise in information management and access, librarians can also contribute to developing robust data governance policies that protect user privacy and prevent discrimination. Overall, librarians have a unique opportunity to ensure that AI development is conducted responsibly and ethically, promoting the well-being of individuals and society.

In addition to developing and improving AI technology, it is equally important to promote educational initiatives that enhance the public's understanding of this field. One way to achieve this is through organizing workshops or seminars by librarians, where experts can share their insights and knowledge on various aspects of artificial intelligence. These workshops can address misconceptions about AI technology and cover its potential benefits, ethical considerations, and limitations. By doing so, the public can gain a more nuanced understanding of AI, which will help them better navigate the rapidly changing technological landscape and make informed decisions about its use.

Challenges and Limitations Faced by Librarianship in Shaping Debates on AI

While librarianship has immense potential to shape debates on emerging technologies like AI, it faces certain challenges:

One of the major challenges in the field of Artificial Intelligence (AI) is related to bias within libraries themselves. It is important to note that library bias can impact how resources are selected or presented to users. 

Though librarians are known for their impartiality and objectivity, they must remain vigilant against their preferences when curating collections on AI. Librarians must ensure that diverse perspectives on AI are adequately represented in their groups. This will not only help to provide a more complete understanding of the topic but also ensure that the users are presented with a balanced view of the subject. Therefore, it is pertinent that librarians take the necessary steps to mitigate any potential bias in their collections and ensure that their readers are inclusive of all perspectives.

In the fast-paced world of AI research, one of the biggest challenges professionals face is accessing accurate and up-to-date information. Keeping up with the latest developments in the field can be a daunting task, as the technology is evolving rapidly. To bridge this gap, librarians and other professionals must develop strategies for continuous learning and collaboration with experts in the field. By staying informed and well-connected, they can ensure that they have access to reliable resources and can keep pace with the latest advancements in AI research.


Wednesday, June 14, 2023

Easy Zero-Shot Prompting ChatGPT Sentiment

Exploring the Power of Zero-Shot Prompting in Language Model Librarianship

Summary

  • In conclusion, Zero-Shot Prompting is a powerful feature in modern LMs that allows them to perform tasks without having been explicitly trained on similar examples.
  • Its potential applications in librarianship are vast, from sentiment analysis to categorization tasks.
  • However, it's important to recognize when zero-shot might not be the best choice, and additional examples or demonstrations may be required for optimal performance.
  • Understanding and utilizing such capabilities become increasingly essential as we leverage AI in libraries.

Problem being addressed

The advancement of AI and language models, such as ChatGPT, has revolutionized how information is comprehended and organized in libraries.

However, not many people know these models' full capabilities, particularly the remarkable potential of Zero-Shot Prompting. This exclusive feature allows LMs to carry out tasks without prior exposure to similar examples, and it is a feature that should receive more recognition.

Understanding Zero-Shot Prompting

Zero-Shot Prompting is a method that allows LMs, trained on large quantities of data, to handle novel tasks without previous examples. This is achieved due to the model's ability to generalize from its training data to unseen scenarios.

In other words, when provided with a task, the model can infer what's needed without being explicitly shown examples of the same task before. This can be particularly useful in librarianship where queries and tasks can be diverse and unpredictable.

Effectiveness of Zero-Shot Prompting

The effectiveness of Zero-Shot Prompting has been well-demonstrated across various scenarios. A prime example is the task of sentiment analysis, which is frequently utilized to comprehend user feedback or text reviews.

The model can accurately carry out this classification by presenting the prompt "Classify the text into neutral, negative, or positive," even if it has never encountered this prompt.

Let's take an example:

Prompt: "Classify the text into neutral, negative, or positive." Text: "I think the vacation is okay." Sentiment: Neutral

In this case, the model correctly identifies the sentiment as neutral, demonstrating the zero-shot capabilities.

When Zero-Shot Prompting Doesn't Work

Please keep in mind that Zero-Shot Prompting can be challenging. There may be situations where this method needs to produce the most accurate outcomes. In these cases, it is advisable to use few-shot prompting instead.

This method involves providing the model with a few examples to help it generate more precise responses. It strikes a balance between the no-example zero-shot and the many-example fine-tuning.

Example ChatGPT sentiment prompt

PromptTextOutput
Classify the text into neutral, negative, or positiveI think the vacation is okayNeutral
Classify the text into neutral, negative, or positiveThis is the best day ever!Positive
Classify the text into neutral, negative, or positiveI didn't like the food at the restaurantNegative

References:

OpenAI. (2020). Language Models are Few-Shot Learners. ArXiv, abs/2005.14165.

Explore ChatGPT for Free | Quick Start Guide for Librarians and Researchers

How to play with ChatGPT for free when you are afraid to ask

Here is a step-by-step guide designed specifically for our librarians and researchers who are curious and would like to play.

Have Fun, and don't pay for ChatGPT Training when free!

  • Navigating the OpenAI Landscape: 
    • Creating an Account
    • Visit https://www.openai.com and create your account today!
    •  Remember to confirm your email for a seamless experience.


Show Me A Video Please



  • The OpenAI Playground
    • After you make your account head over to OpenAI Playground.
    • Sign in with your OpenAI account and select your AI model - ChatGPT, for instance.


Show Me Video Please



Unraveling the Mysteries of ChatGPT:

Generating Responses with ChatGPT

Once you are on https://playground.openai.com, you can explore ChatGPT.

            If you need help with what to ask, you can use some of ours from our quick start prompt guide.

            https://www.chatgptlibrarian.com/2023/03/quick-text-guide-to-making-and-judging.html

            Or find prompts on some websites we reviewed.

                        https://www.chatgptlibrarian.com/search?q=prompt+websites


Friday, May 19, 2023

ChatGPT and The Custom Education to Come

The incorporation of ChatGPT into the educational domain has the potential to transform the conventional information-seeking model. 

ChatGPT can provide students with immediate access to information and answers to their queries.

This platform expands the traditional role of libraries and librarians by offering a digitized, user-friendly, and effective tool that democratizes access to knowledge. 

ChatGPT enables users to access a wide range of information and resources previously only available in physical libraries. This platform is a game-changer for those who seek knowledge and information in a fast and efficient manner.

Another critical advantage of ChatGPT in information seeking is its ability to cater to individual student learning needs. Learners may have diverse educational preferences and grasp concepts at varying paces. 

ChatGPT, with its capacity for understanding and generating nuanced responses, can provide tailored information that aligns with each student's unique learning curve. This aspect contributes to creating more personalized and engaging learning experiences, making information-seeking not just a task but an exciting journey of discovery.

Customizing learning pathways is an essential aspect of modern education. Educators can create a more engaging and effective learning environment by tailoring the learning experience to each student's needs and preferences. This approach allows students to learn at their own pace and in a way that suits their unique learning style. Additionally, personalized learning pathways help to identify areas where students may be struggling and provide targeted support to help them succeed.

Fostering independent learning is a crucial aspect of education. It involves equipping students with the necessary skills and resources to take charge of their learning. In addition, independent learning allows students to develop critical thinking skills, problem-solving abilities, and self-motivation. 

Teachers can foster independent learning by providing opportunities for students to explore their interests, encouraging them to ask questions, and guiding them toward resources that can help them learn independently. By fostering independent learning, teachers can help students become lifelong learners capable of adapting to new challenges and confidently pursuing their goals.

The instant and customizable responses from ChatGPT are invaluable tools in promoting independent learning. As students interact with ChatGPT, they learn to formulate their inquiries efficiently and interpret the generated responses effectively. This process enhances their research skills, comprehension abilities, and critical thinking. 

Thursday, May 18, 2023

The LLama Effect: Impressive Open Source Alternatives to ChatGPT

How an Accidental Leak Sparked a Series of Impressive Open-Source Alternatives to ChatGPT

Background

The open-source model has demonstrated viability in generative AI, particularly text-to-image models. Recently, the same level of success has been observed in the large language model (LLM) space, with the accidental leak of the LLM known as LLama. This inadvertent release has brought to light the potential of open-source models in the LLM space. The LLama model has exhibited promising results in generating coherent and contextually relevant text, which has significant implications for natural language processing and generation. The success of the LLama model underscores the importance of open-source models in advancing the field of AI and making it more accessible to researchers and developers.

Implications for Librarians

As the landscape of Large Language Models (LLMs) such as LLama, GPT-4, and others continues to evolve, the role of librarians in educating and facilitating users' understanding of these models becomes crucial. In addition, with the emergence of open-source alternatives, there is likely to be increased user interest and inquiries. Librarians can help guide these inquiries by familiarizing themselves with these models' capabilities and potential uses.

By comprehending and leveraging these models, librarians can significantly enhance the library's role in fostering knowledge and understanding of this critical field.

How might these advancements impact librarians?

Resource Guidance


Libraries could play a crucial role in providing resources related to AI and machine learning, both online and offline. With the increasing popularity of open-source models like LLama and its derivatives, librarians can assist users in finding appropriate resources to understand these technologies. This could include academic papers, books, tutorials, or even links to open-source software and codebases. By offering access to a wide range of resources, libraries can help individuals stay up-to-date with the latest developments in AI and machine learning and ultimately contribute to the growth and advancement of these fields.
Facilitating Learning

As with any technical topic, the learning curve for understanding LLMs can be steep. However, librarians can play an essential role in helping users navigate this learning process. This could involve directing users toward essential resources, explaining basic concepts, or helping them access online courses or workshops related to LLMs. By doing so, librarians can empower users to develop the skills and knowledge necessary to effectively utilize LLMs in their research and work. Additionally, librarians can serve as a valuable resource for troubleshooting issues or answering questions that may arise during the learning process. Overall, the support and guidance librarians provide can make a significant difference in helping users overcome the challenges associated with learning about LLMs.

Anticipating Future Trends

As AI evolves, it brings new technologies, applications, and ethical considerations. Librarians, as information professionals, should strive to stay ahead of these trends to prepare for future user inquiries. This means keeping up-to-date with the latest developments in AI and related fields and understanding the potential implications of these technologies for society. By doing so, librarians can better serve their users and help them navigate the complex landscape of AI and its impact on our world. The implications of these open-source models extend beyond just user inquiries and education. They also impact how libraries function. With the increasing availability of open-source materials, libraries may need to adapt their collections and services to meet the changing needs of their patrons. Additionally, using open-source models may lead to greater collaboration and sharing of resources among libraries, ultimately benefiting the entire community. As such, libraries must stay informed about these developments and be prepared to embrace new approaches to serving their users.

Information Discovery and Retrieval

LLMs, or Language Models, are practical tools for processing and understanding text. They could revolutionize how we search for information in libraries. LLMs can provide more accurate and relevant search results by understanding natural language queries. Additionally, LLMs can provide more contextually aware search results, which is especially useful in research contexts. Overall, the use of LLMs in libraries has the potential to significantly improve the efficiency and effectiveness of information retrieval.

Cataloging

AI models can automate or augment aspects of the cataloging process. For example, providing more accurate or detailed tagging and classification of resources can lead to more accessible and efficient discovery. This can significantly benefit organizations that deal with large amounts of data and information, such as libraries, archives, and museums. With the help of AI, these institutions can streamline their cataloging processes and make their resources more accessible to the public.

User Engagement

Libraries can leverage LLMs to provide interactive and personalized experiences to their users. In today's world, Artificial Intelligence (AI) has become an integral part of our lives. One of the most significant applications of AI is in the field of conversational systems. With the help of AI-based systems, users can have conversations to get reading recommendations, clarify their doubts, or get help with research. These experiences can drive user engagement and satisfaction, making it a win-win situation for both the user and the system. As AI continues to evolve, we can expect conversational systems to become even more sophisticated, providing users an even better experience.

Information Discovery and Retrieval

As AI models become more sophisticated, they are increasingly capable of understanding and generating human-like text. This could revolutionize how information is discovered and retrieved in libraries. For instance, users could interact with an AI-based system that understands natural language queries and provides accurate results. Furthermore, the system could even suggest related topics or materials based on the context of the queries, making the search process more efficient and effective. With the help of AI, libraries could become more accessible and user-friendly, providing a wealth of knowledge at the fingertips of anyone with an internet connection.

Ethical Considerations

The rise of LLMs (Language and Learning Machines) presents various opportunities for libraries and their users. However, these opportunities come with ethical considerations that must be addressed. Issues such as data privacy, security, and the potential misuse of AI are significant and must be addressed. As librarians, we educate users about these issues and promote responsible use of AI technologies. By doing so, we can ensure that the benefits of LLMs are maximized while minimizing any potential negative consequences.

Professional Development

Given these developments, librarians may need new skills to stay relevant. Therefore, understanding the basics of AI, machine learning, and LLMs may become increasingly important. This understanding can help librarians guide users more effectively and leverage these technologies to improve library services. Librarians must keep up with the latest trends and developments as technology advances. By gaining knowledge in AI, machine learning, and LLMs, librarians can better serve their users and provide more efficient and effective library services. With these skills, librarians can guide users in navigating the ever-changing landscape of technology and help them find the information they need.

Main Points

Meta AI announced an LLM called LLama, which showed performance comparable to GPT-3 despite its smaller size.

Meta AI has recently launched its new language model, LLama. Despite its relatively smaller size, LLama has demonstrated performance comparable to GPT-3. This development is highly significant for natural language processing, as it suggests that smaller models may be capable of achieving results similar to their larger counterparts. It will be intriguing to observe how LLama progresses and what implications it will have on the future of AI language models.

LLama was accidentally leaked on 4chan, leading to widespread downloading and a surge of open-source innovation.

Llama was inadvertently disclosed on 4chan, resulting in extensive downloads and a surge of open-source innovation. Numerous users who value its distinctive features and user-friendly interface have widely adopted this innovative software. Despite its modest origins, Llama has rapidly gained popularity among those seeking a dependable and efficient tool for their daily tasks. Its success can be attributed to the diligent efforts and unwavering commitment of its developers, who persistently enhance and refine the software to cater to the requirements of its expanding user community.

Several advanced LLMs built on LLama, such as Alpaca, Vicuna, Koala, ChatLLama, FreedomGPT, and ColossalChat, have since been developed and released. 

Several advanced LLMs, such as Alpaca, Vicuna, Koala, ChatLLama, FreedomGPT, and ColossalChat, have been developed and released on the LLama platform. These LLMs have many features and capabilities, including advanced natural language processing, machine learning, and deep learning algorithms. With the aid of these tools, users can analyze and comprehend complex data sets, generate high-quality content, and communicate more effectively with their audiences. Furthermore, as AI continues to evolve, we will probably witness the emergence of even more sophisticated LLMs built on LLama and other platforms in the future.

Stanford University released Alpaca, an instruction-following model based on the LLama 7B model.

Stanford University has recently unveiled a new instruction-following model named Alpaca. This model, built on the foundation of the LLama 7B model, has been designed to enhance the accuracy of natural language processing tasks. Alpaca is expected to be particularly beneficial in applications such as question answering, dialogue systems, and machine translation. With its advanced capabilities, Alpaca is poised to make a significant impact in the field of artificial intelligence and natural language processing.

Researchers from UC Berkeley, CMU, Stanford, and UC San Diego open-sourced Vicuna, which matches the performance of GPT-4.

Researchers from UC Berkeley, Carnegie Mellon University (CMU), Stanford University, and UC San Diego have recently made Vicuna an open-source tool. This new software can match the performance of GPT-4, a state-of-the-art language model. Vicuna's release is expected to significantly impact the natural language processing (NLP) field, providing researchers with a powerful new tool for developing and testing language models. With the open-source release of Vicuna, the research community now has access to a cutting-edge NLP tool that can help drive innovation and advance the field.

The Berkeley AI Research Institute released Koala, fine-tuned using internet dialogues.

The Berkeley AI Research Institute has recently unveiled a new language model, Koala, which has been fine-tuned using internet dialogues. This model has been trained on a vast dataset of online conversations, making it a powerful tool for natural language processing tasks, including text generation and language translation. With its advanced capabilities, Koala has the potential to revolutionize the field of artificial intelligence and bring us closer to achieving human-like language understanding.

Nebuly released ChatLLama, a framework for creating conversational assistants.

Nebuly has recently launched ChatLLama, a framework specifically designed to create conversational assistants. This innovative tool is expected to revolutionize our interactions with technology, enabling more natural and intuitive communication between humans and machines. With ChatLLama, developers can effortlessly build chatbots and virtual assistants that can comprehend and respond to human language, thereby simplifying the process of providing customer support, automating tasks, and enhancing the overall user experience. The release of ChatLLama is a significant milestone in conversational AI, and it is anticipated to profoundly impact how we interact with technology in the future.

FreedomGPT is an open-source conversational agent based on Alpaca based on LLama.

FreedomGPT is a conversational agent operating on an open-source platform based on Alpaca and LLama. Its primary objective is to provide users with a seamless and natural language processing experience. The platform is built on cutting-edge machine-learning algorithms that enable it to understand and respond to user queries in real time. As a result, FreedomGPT is a versatile tool that can be used for various applications, including customer service, education, and entertainment. The platform continuously evolves, with new features and capabilities regularly added to enhance the user experience.

UC Berkeley's Colossal-AI project released ColossalChat, a ChatGPT-type model with a complete RLHF pipeline based on LLama.


The Colossal-AI project at UC Berkeley has recently unveiled ColossalChat, a ChatGPT-type model with a complete RLHF pipeline based on LLama. This innovative model is poised to revolutionize the field of conversational AI, as it can generate human-like responses to a wide range of prompts. With its advanced language processing capabilities, ColossalChat has the potential to be utilized in a variety of applications, ranging from customer service chatbots to virtual assistants. The release of this model represents a significant milestone in the advancement of AI technology and is expected to have a profound impact on the industry.

Citations: 

- The Sequence. (2023). The LLama Effect: How an Accidental Leak Sparked a Series of Impressive Open Source Alternatives to ChatGPT. Retrieved from https://thesequence.substack.com/p/the-llama-effect-how-an-accidental.