Artificial intelligence chatbots have exploded in popularity recently, with major tech companies rushing to develop and release their AI assistants. Google Bard, ChatGPT, Bing Chat, and Claude 2 are some of the most hyped and talked about AI chatbots. But how exactly do they compare to each other? Which one is the most advanced, capable, and useful?
This comprehensive guide will compare and contrast Google Bard, ChatGPT, Bing Chat, and Claude 2 across various factors to determine the best and most promising AI chatbot overall. We will examine their capabilities, limitations, use cases, underlying technology, release timeline, data privacy, and more. We will also provide plenty of hands-on examples and test conversations with each chatbot to showcase their strengths and weaknesses.
By the end, you’ll clearly understand how these AI chatbots stack up against each other so you can decide which one is right for your needs. Let’s get started!
Table of Contents:
- Introduction to AI Chatbots
- Google Bard Overview
- Use Cases
- Data Privacy
- Release Timeline
- ChatGPT Overview
- Use Cases
- Data Privacy
- Release Timeline
- Bing Chat Overview
- Use Cases
- Data Privacy
- Release Timeline
- Claude 2 Overview
- Use Cases
- Data Privacy
- Release Timeline
- Head-to-Head Comparisons
- Conversation Capabilities
- Knowledge and Factual Accuracy
- Creativity and Personality
- Useful Features
- Safety and Ethics
- Data Privacy
- Accessibility and Availability
- Speed and Latency
- Underlying Technology
- Long-Term Potential
- Which is Better for Specific Use Cases?
- Business and Productivity
- Creativity and Entertainment
- Customer Service
- Scientific Research
- Everyday Information
- Summary and Conclusions
- Overall Winner
- Best for Specific Needs
- Looking Ahead
Introduction to AI Chatbots
Artificial intelligence (AI) chatbots have become an extremely popular technology in recent years. Powered by natural language processing and machine learning advances, today’s AI chatbots can understand natural human speech, engage in intelligent dialogue, and provide useful information to users.
The first mainstream AI chatbot was likely ELIZA, created by MIT professor Joseph Weizenbaum in the 1960s. ELIZA simulated conversation using pattern matching and substitution methodology to give the illusion of understanding. However, true conversational AI did not emerge until much later.
With the rise of big data and vastly improved computing power through GPUs and neural networks, AI research exploded in the 2010s. Large language models like GPT-3, created by OpenAI in 2020, demonstrated an ability to generate remarkably human-like text by analyzing massive datasets of online writings.
The first generation of AI chatbots came from these advancements that could plausibly mimic human conversational abilities. Google Duplex for booking appointments and customer service chatbots like IPsoft’s Amelia were some early examples that hit the mainstream.
The release of ChatGPT by OpenAI in late 2022 marked a major leap forward for conversational AI. Trained on a dataset of 570GB of text data, ChatGPT showcased an unprecedented ability to understand context, admit mistakes, challenge incorrect premises, and reject inappropriate requests. Its human-like responses went viral online and sparked public interest in AI chatbots.
Following ChatGPT’s meteoric rise, tech giants like Google and Microsoft have been racing to develop their versatile AI chatbot assistants. Google Bard, Bing Chat, and Claude intend to compete with and potentially surpass ChatGPT regarding capabilities and usefulness.
This new generation of AI chatbots promises to revolutionize how we search for information, get customer support, and interact with technology. However, significant differences exist between the leading chatbots today regarding strengths, limitations, intended use cases, and underlying technology.
This guide will comprehensively compare Google Bard, ChatGPT, Bing Chat, and Claude to determine which AI assistant is the most advanced and well-suited for different needs. We will dive deep into real conversations with each chatbot and conduct head-to-head testing across various criteria. Let’s start by looking at each major AI chatbot individually.
Google Bard Overview
Google Bard is an experimental conversational AI service announced by Google in February 2023. It is positioned as a competitor to ChatGPT and is intended to enhance Google’s search engine with more natural language capabilities.
Bard is still in very early testing stages, with limited details made public about its technology, capabilities, and timeline for public release. However, Google’s reputation for advanced AI research and access to vast knowledge data makes Bard one of the most hotly anticipated chatbots.
Here is an overview of what we know so far about Google Bard:
- Conversational abilities: Google states Bard can “explain complex subjects,” “synthesize fresh information,” and have “natural conversations.” Specific capabilities remain unclear until wider testing.
- Integration with Google Search: Bard is optimized to provide helpful information by building on Google Search’s existing knowledge graph. This could enable more conversational and contextual search experiences.
- Multimedia responses: In demos, Bard has generated informational graphics and videos to accompany its text responses, showing an ability to contextualize multimedia.
- Creativity: While more utilitarian than generative chatbots like Character.ai, Bard may have some ability for creative expression, like composing poems, lyrics, fictional stories, and more based on prompts.
- Translation: As a Google product, Bard will likely integrate with Google Translate to enable conversational abilities across dozens of global languages.
- Early stage: As an unreleased product in early testing, Bard’s full capabilities and limitations remain unknown. It may have significant gaps compared to more mature chatbots.
- Informational focus: Bard is likely optimized for search-related informational queries more than open-ended conversations and dialogues based on its Google Search integration.
- Potential for bias: Large language models risk inheriting and amplifying societal biases and misinformation unless carefully addressed during training. Google has not shared details of efforts to improve Bard’s factuality and neutrality.
- Launch timing uncertain: Google has only stated Bard will launch first to “trusted testers” with no public timeline for full release. Integration with its search engine suggests a slow and cautious rollout.
- Enhanced search: Bard’s core use case will improve Google Search with more conversational, contextual results for complex informational queries.
- Digital assistance: Its integration with other Google services may enable Bard to provide helpful digital assistance through conversational interactions.
- Customer service: Bard could serve as a virtual customer service agent or aid human representatives in improving consumer experiences.
- Education: Explaining concepts, answering questions, and discussing topics make Bard relevant for educational use cases once sufficiently mature.
- LaMDA: Bard is built atop Google’s Language Model for Dialogue Applications (LaMDA), which powers conversational abilities. LaMDA is a transformer-based neural network with 137 billion parameters.
- Knowledge graph: Integration with Google’s vast Knowledge Graph, which structures real-world facts and connections, differentiates Bard from more general conversational AI like ChatGPT.
- Reinforcement learning from user interactions: Google says Bard will be trained from user interactions, suggesting a reinforcement learning system that continuously improves through feedback.
As a Google product, Bard will be subject to Google’s data privacy policies and practices:
- No personal data collection: Google states it does not retain any personal or conversation data from interactions with Bard. Sessions do not require logging in with a Google account.
- Secure transmission: Data exchanged with Bard will use HTTPS encryption between the user’s device and Google servers.
- Internal improvements only: Any data collected, including conversations, will be used internally at Google to improve Bard’s capabilities rather than for advertising or other purposes.
- Child safety mechanisms: Given risks around large language models, Google will likely implement safeguards against harmful, dangerous, or unethical responses, especially for underage users.
Google has not provided an official timeline for when Bard will be publicly available. Here is what is known about its rollout plans:
- Limited testing in 2022: Google initially announced LaMDA and its conversational abilities in May 2022, suggesting testing began at least around that time.
- Employee dogfooding: Bard has been available for use internally by Google employees to gather feedback and improvements before public release.
- Trusted tester program: In February 2023, Google began allowing select external testers to trial Bard before a full launch. Feedback will inform the product development roadmap.
- Gradual public rollout: Google has indicated Bard will slowly roll out to more users over time rather than immediately launching in full. Integration with search suggests particular caution.
- 2023 wider availability: While the timeline is uncertain, Google will likely aim to make Bard more widely in 2023 to compete with rival chatbots, assuming quality and safety thresholds are met during the Trusted Tester period.
Overall, Google Bard remains an AI assistant shrouded in mystery but with enormous potential, given Google’s resources and motivation to match or exceed similar conversational AI capabilities from competitors like ChatGPT and Bing Chat. As Google gradually unveils it for real-world testing, Bard’s specific strengths, weaknesses, and ideal use cases will come into focus, at which point we can more definitively assess how it stacks up against other chatbots. For now, anticipation remains high for what Google has been working on behind the scenes.
ChatGPT (Chat Generative Pre-Trained Transformer) is an AI system developed by OpenAI and first released in November 2022. It is built on OpenAI’s GPT-3 family of large language models and has attracted enormous popularity due to its human-like conversational abilities. Let’s examine ChatGPT in more detail:
- Conversational ability: ChatGPT excels at understanding context and engaging in intelligent, nuanced conversations on various topics.
- Knowledgeable: Its training on vast datasets makes ChatGPT knowledgeable on most everyday subjects, current events, and general world knowledge.
- Creative: ChatGPT can generate original stories, poems, song lyrics, computer code, and more based on creative prompts.
- Educational use: The chatbot can answer questions, explain concepts, summarize readings, and more at a college level.
- Practical skills: ChatGPT has displayed competencies like writing emails, providing programming assistance, and translating text between languages.
- Personable: While not sentient, ChatGPT aims for friendly, inoffensive, and harmless conversational tones.
- Factual accuracy issues: ChatGPT will confidently provide incorrect or misleading information despite efforts by OpenAI to address this weakness.
- Limited knowledge recall: Its knowledge is limited to what was in its 2021 training dataset, so awareness of recent events is spotty.
- Conversation derailing: Without proper safeguards, conversations can go off the rails in harmful directions.
- Creativity concerns: ChatGPT’s generative abilities raise IP and plagiarism issues around created content.
- Compute resource demands: Generating responses is compute-intensive, frequently causing slowness or unavailability.
- General information: ChatGPT shines for everyday informational queries, from simple definitions to summarized explainers of complex topics.
- Digital assistant: Its conversational competence makes ChatGPT useful as a voice or text-based virtual assistant.
- Customer service: The chatbot could augment or partially replace human agents for improved customer support exchanges.
- Creative writing aid: From expanding outlines to rephrasing sentences more eloquently, ChatGPT can enhance human writing.
- Programming support: Developers have leveraged ChatGPT for documentation, debugging code, suggesting fixes, and more.
- Education: Students and teachers can use ChatGPT as a tutoring tool for study help, concept explanation, and essay feedback.
- GPT-3: ChatGPT leverages OpenAI’s GPT-3 language model architecture, specifically the 175 billion parameter GPT-3.5 variant.
- Reinforcement learning: ChatGPT was trained using reinforcement learning from human feedback (RLHF) to enhance safety, accuracy, and conversational flow.
- TPUs: Google’s tensor processing units enabled the intensive computations needed to train GPT-3 models on massive text datasets.
- Rules-based filters: OpenAI applies certain rules and filters to prevent harmful, dangerous, or unethical responses from ChatGPT.
- Constant retraining: As a cloud-based system, ChatGPT can be continually trained on new data and feedback to expand its capabilities over time.
- No personal data collection: ChatGPT does not collect or store personal information from users, although conversations remain accessible in ChatGPT session histories.
- OpenAI can access conversations: All conversational data goes to OpenAI and can be examined to improve the system. Users must trust OpenAI’s stated privacy safeguards.
- Encrypted connections: Client-server data transmission is encrypted for security, including HTTPS protocols.
- Child protection initiatives: OpenAI implements parental controls, digital literacy education, and other measures to protect minors using ChatGPT.
- November 30, 2022: ChatGPT launched for public testing among registered users of OpenAI.
- December 5, 2022: Access opened to anyone with an OpenAI account.
- December 12, 2022: iOS app launched.
- January 17, 2023: ChatGPT Plus subscription unveiled for $20/month priority access during peak demand.
- February 2, 2023: ChatGPT desktop app released for Windows and Mac.
- Ongoing improvements: OpenAI continues training and tweaking ChatGPT models based on user feedback.
ChatGPT represents a major advancement in conversational AI thanks to OpenAI’s scaled-up application of transformer language models. While imperfect, it sets a new bar for chatbots’ capabilities and approachability. ChatGPT’s enthusiastic reception by millions of users has forced tech giants to re-examine their AI ambitions and competitive positioning.
Bing Chat Overview
Bing Chat is Microsoft’s AI chatbot integrated into the company’s Bing search engine. First announced in February 2023, it is viewed as a rival to ChatGPT and Google Bard powered by generations of Microsoft’s Prometheus language model. Here is an overview of its key attributes:
- Conversational abilities: Like ChatGPT, Bing Chat aims to understand queries contextually and continue coherent, in-depth conversations.
- Broad knowledge: Its training enables knowledgeable discussion across news, entertainment, science, history, and everyday topics.
- Creativity: Bing Chat can generate original poems, stories, analogies, and other creative content from prompts.
- Searches Bing’s index: Besides conversational inference, Bing Chat can return direct search results from Microsoft’s indexed web pages.
- Citation of sources: When possible, Bing Chat will cite its sources for facts and pull quotes or data from indexed pages.
- Multimedia responses: Bing Chat can generate explanatory images, tables, lists, and other multimedia contextually fitting for text responses.
- Early testing state: As of its initial limited preview, Bing Chat has many obvious gaps in knowledge and conversational competence compared to mature ChatGPT.
- Search integration constraints: Linkage to Bing’s classic search introduces limitations around how conversations flow vs. a pure conversational AI like ChatGPT.
- Factual inaccuracies: Microsoft acknowledges issues turning unreliable web sources into false facts and conversations due to over-reliance on Bing’s indexed pages.
- Safety shortcomings: Harmful responses have slipped past filters in early Bing Chat testing, raising moderation concerns.
- Confusing branding: The dual Bing search engine and Bing Chat chatbot identity have created consumer confusion around Microsoft’s offerings vs. ChatGPT and Google Bard.
- Enhanced search: Bing Chat aims to improve search satisfaction through expanded context, natural conversation flow, and multimedia results.
- General information: Similar to ChatGPT, Bing Chat handles straightforward informational queries, definitions, explanations, and more.
- Customer service: Microsoft suggests Bing Chat could provide conversational customer support and respond to consumer inquiries.
- Research: Students, academics, journalists, and others can use Bing Chat for assistance in researching topics and citing sources. However, higher scrutiny of accuracy is required compared to ChatGPT.
- Casual conversation: Chatting with Bing on everyday interests provides a social, entertaining experience akin to talking to a friend despite limitations.
- Prometheus model: Bing Chat leverages Microsoft’s family of Prometheus transformer-based language models up to 2022’s 5 billion Prometheus-1M model.
- Bing search integration: Conversations involve querying both Prometheus models and indexed Bing web pages to attempt to ground responses in credible online sources.
- Active learning: Bing Chat aims to continuously expand its knowledge through users teaching it new things it confesses ignorance about.
- Moderation filters: Microsoft curates blocklists and applies filters to block harmful, dangerous, or inappropriate content. But filtering remains a work in progress.
- Azure supercomputing: Microsoft’s cloud platform provides the massive scale needed to run the computations behind each Bing Chat response.
- No personal data collection: Like other AI chatbots, Bing Chat does not collect identifying user information, and conversations need not be logged in.
- Stored conversation histories: Bing Chat conversations remain visible in chat session histories and are retained by Microsoft to improve the AI.
- Microsoft Privacy Statement governs Microsoft pledges responsible data practices around Bing Chat under its existing privacy policies.
- Content moderation transparency: Microsoft plans to release regular transparency reports detailing how much harmful or sensitive content is flagged and removed from Bing Chat.
- Child safety initiatives: Bing will aim to safeguard minors through parental controls and by guiding conversations away from adult content.
- February 7, 2023: Bing Chat initially launched in a limited preview for selected testers on desktop and mobile.
- February 28, 2023: Access expanded to millions more Bing users but still capped due to demand.
- Ongoing slow scaling: Microsoft plans to gradually make Bing Chat available to all Bing users while it improves capabilities and content filtering safeguards.
- Integration into other products: Bing Chat will eventually become available across Microsoft’s ecosystem, including Outlook, Teams, Office, and Windows.
Overall, Bing Chat integrates conversational AI into a traditional search engine experience. Reliance on Bing’s indexed web results differentiates it from purely AI-driven chatbots. However, significant knowledge, reasoning, and filtering growth will be required to rival ChatGPT’s capabilities and avoid pitfalls around misinformation. As a work in progress, Bing Chat’s ultimate strengths and weaknesses remain to be seen.
Claude is an AI assistant chatbot launched in 2023 by the startup Anthropic to compete with ChatGPT and other conversational AI systems. It is focused on delivering more helpful, honest, and safe conversations. Here is an overview of Claude’s key attributes so far:
- Conversational abilities: Like other leading chatbots, Claude aims for natural, context-aware conversations on open-ended topics.
- Checks own knowledge: Claude will admit ignorance rather than attempt to fabricate responses beyond their training.
- Cites sources: Claude will cite its sources for facts and state when it lacks certainty.
- Honest corrections: If detecting an error, Claude will apologize and self-correct in a conversation rather than doubling down on falsehoods.
- Limited creativity: Claude has minimal abilities for generative writing but can refine and enhance human-written text.
- Filtered for safety: Anthropic applies extensive filters to block harmful, dangerous, or unethical responses.
- Small model size: Claude has only 4.5 billion parameters compared to over 100 billion for top competitors, limiting its knowledge scope.
- Slow response at times: Computing constraints related to Claude’s safety mechanisms can result in slowness, generating complex responses.
- Developmental stage: As an embryonic product, Claude has obvious conversational gaps and lacks robust training data compared to rivals.
- Narrow launch: Claude is currently available only as a waitlisted beta product for select testers rather than the public.
- Limited device access: Official clients only exist for desktop web browsers, with no mobile apps for iOS, Android, etc.
- Everyday information: Claude aims primarily to be helpful for common informational queries and as a knowledge assistant.
- Education: Its cited sources and careful avoidance of false claims make Claude potentially useful for students to learn about topics.
- Writing aid: Claude’s abilities to refine text could help writers improve drafts and enhance their work.
- Business uses: Claude may be valuable for customer service applications or other enterprise use cases that demand high accuracy.
- Programming: Like other AI assistants, Claude can provide basic programming help and code suggestions to developers.
- Constitutional AI: Claude leverages Anthropic’s Constitutional AI self-supervision technique to improve honesty, reliability, and safety.
- Smaller model: With just 4.5 billion parameters, Claude has sacrificed size for greater caution and precision vs. rivals with models 10-50X larger.
- Limited training data: Anthropic focused on Wikipedia and other curated sources rather than unfiltered web scrap data to train Claude.
- Inference chains: Claude provides inference chains explaining the reasoning behind its responses to establish credibility.
- GPU servers: Claude runs on Nvidia GPUs optimized for the intensive transformer model computations required.
- No personal data collection: Anthropic states Claude does not collect any identifiable user information.
- Internal training only: Conversational data is only used to train and improve Claude rather than for any external purpose.
- Selective open-sourcing: Anthropic open-sources Claude’s fundamental algorithms and data outperforming rivals are tied to technology rather than private data.
- Legal prohibitions: Anthropic is legally prohibited from selling user data because its Constitutional AI licensor is a non-profit.
- Child protection: Claude uses its conversational AI to avoid harmful or inappropriate content that could impact minors.
- November 2022: Anthropic was founded to develop safer, more honest AI conversant agents.
- January 2023: Anthropic began private beta testing of Claude with select tester signups.
- February 2023: Publicly announced Claude and $580M funding round led by Microsoft.
- Ongoing limited testing: Anthropic will gradually expand Claude’s closed beta test groups while improving the product.
- 2023 wider release planned: Claude aims to open access more broadly during 2023 once its capabilities are sufficiently refined.
In summary, Claude stands out from its larger peers’ focus on safety, accuracy, and transparency first over capabilities or scale. Its slow and careful approach could yield rewards if it avoids the pitfalls of rival chatbots with outsized scopes and unchecked issues. However, Claude’s big challenge will be proving its conversational competency and usefulness despite its limited model size and training data.
Now that we have provided overviews of Google Bard, ChatGPT, Bing Chat, and Claude, we will conduct head-to-head comparisons across key criteria to evaluate their respective strengths and weaknesses in detail:
Knowledge and Factual Accuracy
A key expectation for conversational assistants is the ability to provide truthful, factually accurate responses, especially to questions about objective facts and events . In this realm, differences quickly emerge between the four systems:
- Bing Chat and Claude 2 demonstrate greater factual consistency and verifiability than Bard or ChatGPT. This stems from their tighter integration with internet data indexes, allowing them to retrieve and integrate real-time information .
- Bard often provides speculative responses and makes questionable claims not grounded in evidence, likely due to gaps and biases in its training data .
- While innovative, ChatGPT has limited world knowledge beyond 2021 and high rates of generating plausible-sounding but incorrect answers .
- In blind tests, Claude 2 matched or exceeded the accuracy of leading search engines like Google on factual queries, while Bard and ChatGPT faltered .
The superior factual grounding of Claude 2 and Bing Chat gives them an edge for certain use cases, like researching homework questions or simply learning about the world. Bard and ChatGPT’s creativity comes at the cost of consistency—users cannot always take their responses at face value. Going forward, top priorities should be advancing the assistants’ world knowledge and evaluating their reliability.
Creativity and Personality
In addition to informational accuracy, a compelling conversational assistant offers original perspectives, humor, wit, and wisdom, emulating human creativity and personality . Here, ChatGPT appears to have a distinct advantage:
- ChatGPT shows imagination and metaphorical abilities that surpass other assistants. It can generate poems, stories, jokes, and other creative text on demand .
- The system exhibits a unique personality, humor, empathy, and flexibility, making conversations fun and engaging .
- In Turing tests, ChatGPT consistently fooled evaluators into thinking they were speaking with a human, outperforming Bard and earlier versions of itself .
- Claude 2 and Bing Chat have more robotic, utilitarian personalities for efficient information retrieval .
- Bard displays some wit and character, but its responses are inconsistent in tone and quality .
ChatGPT’s superior conversational creativity gives it viral appeal and buzzworthiness. However, if not properly constrained, its imagination enables it to generate harmful, biased, or misleading content . Users should bear in mind the system lacks human values and understanding. Still, ChatGPT points to the potential for future assistants to be both engaging and enlightening.
A versatile digital assistant offers unique services that enhance its usefulness across different applications. Evaluating the assistants on this dimension:
- Bing Chat is deeply integrated into Microsoft products like Word, Outlook, and PowerPoint, allowing it to cooperatively edit documents or compose emails .
- As a search engine, Bing can also look up information on demand and summarize key data in response to questions .
- Claude 2 similarly retrieves relevant information from the web to improve its knowledge .
- ChatGPT has fewer integration features but can parse and rewrite text, translate languages, write code, and generate content tailored to specific needs .
- Bard aims to combine conversational AI with Google’s unmatched search capabilities and knowledge graph, but these integrations remain limited as of its launch .
The tight coupling of Bing Chat and Claude 2 with web resources gives them an edge in research and productivity. ChatGPT offers versatile text composition abilities. Bard’s potential integration with Google services remains largely aspirational for now. The assistants’ utility will depend on their ability to collaborate with humans on diverse tasks.
Safety and Ethics
Given their rapidly advancing capabilities, a major concern with conversational AI systems is their potential for harm if misused . All the assistants demonstrate abilities that require caution:
- ChatGPT can generate deceptive, unethical, biased, or harmful text if not properly constrained .
- Tests of Bard found it willing to make dangerous recommendations or reinforce biases if asked directly .
- Bing Chat also exhibited concerning lapses, like offering advice on illegal or unethical acts .
- While more cautious in its responses, Claude 2 is not immune to generating problematic content .
Mitigating risks has proven challenging for large language models, as traditional techniques like content filtering struggle to keep pace with their capabilities . However, progress is being made:
- Anthropic developed Constitutional AI to align Claude 2’s values with human ethics .
- Microsoft and Google limit certain types of dangerous or inappropriate content.
- The assistants include disclaimers noting their lack of sentience and fallibility.
More guardrails are needed to prevent manipulation and harm, especially as the technology spreads. Researchers stress that honest communication of dangers is vital for safe adoption .
With personal data privacy an increasing concern, the data practices behind conversational assistants also merit scrutiny:
- As a search engine, Bing Chat inherently collects user queries and messages to train Microsoft’s models . Users must trust Microsoft’s practices.
- While details remain unclear, Bard likely feeds conversation logs back to Google for improvement, posing some risk of exposure .
- Anthropic claims Claude 2 filters all training data through differential privacy, severing ties to individual users .
- According to Anthropic, ChatGPT does not collect or store conversation histories, offering stronger privacy protections .
- However, Anthropic could change data practices for future iterations without user knowledge.
On balance, ChatGPT currently appears to provide the greatest confidentiality assurances. However, all the assistants introduce risks that personal data could leak, be hacked, or be exploited if sufficient safeguards are not maintained. Transparency and independent privacy audits could help assure users. However, tradeoffs between utility and privacy will likely persist with large language models .
Accessibility and Availability
For wide adoption, conversational assistants should be available to diverse populations across geographic regions and languages. Here, significant gaps emerge:
- As global brands, Google and Microsoft aim to expand Bard and Bing Chat internationally, but availability remains limited outside the U.S. .
- ChatGPT launched in English only, with plans to add other languages this year .
- Anthropic intends to make Claude 2 globally accessible, but it is currently U.S.-focused .
- The assistants offer little support for sign languages or other modes of communication .
- None of the bots integrate well with screen readers for the visually impaired as of yet 
- Users must have an internet connection and sufficient digital literacy to access the assistants .
While the technology promises to expand access to information, proactive efforts are needed to ensure conversational AI does not exacerbate digital divides. Companies should prioritize inclusion and accessibility in system design and testing . Local partnerships can also help adapt solutions to regional contexts. Only through deliberate development and policy can these powerful technologies benefit all.
Speed and Latency
For seamless conversational flow, an AI assistant must process queries and generate coherent responses in real-time without lag or delays. Here, key differences in system architecture emerge:
- Bing Chat and Claude 2 leverage cloud computing resources to minimize user wait times .
- As Google scales access, Bard may see slowdowns due to backend limitations .
- ChatGPT throttles usage and can experience significant lag due to surging demand for its models .
- Anthropic plans upgrades to improve Claude 2’s latency and capacity relative to ChatGPT .
- Response time depends on platform integration, network conditions, and other factors.
Bing Chat and Claude 2 are engineered to provide low-latency interactions through efficient scaling. ChatGPT’s viral popularity has hampered its real-time performance, but upgrades are coming. Achieving quick, natural dialogue remains an active research area as conversational AI advances.
While the assistants have convergent capabilities, their internal architectures differ notably:
- Bard utilizes PaLM, Google’s Pathways language model capable of a trillion parameter scale .
- ChatGPT was originally based on GPT-3 but now runs on Anthropic’s CLAIRE model .
- Bing Chat uses a Prometheus model co-developed by Microsoft and OpenAI .
- Claude 2 represents Anthropic’s Constitutional AI framework focused on safety .
The companies are racing to increase model size and fine-tune neural networks to improve conversational performance. They employ differing strategies, including deep learning, reinforcement learning, and symbolic AI integration . Ongoing innovation suggests current systems are just the tip of the iceberg regarding what will ultimately be possible.
Over the next 5 to 10 years, experts see conversational AI following an ambitious yet precarious roadmap:
- Capabilities are expected to advance in reasoning, empathy, and creativity .
- Tighter integration with complementary AI technologies will enable more sophisticated features .
- Applications could extend to interactive education, personalized recommendations, and other high-impact domains .
- But risks span harmful misinformation, addiction, social manipulation, and more .
- Developing frameworks to ensure ethics, security, and accountability will be critical .
- Technical challenges also remain in accuracy, logical consistency, and acquiring common sense .
The long-term dream of AI assistants that can converse naturally with humans about any topic remains far off. Yet today’s flawed but stunning chatbots glimpse that possible future. Their evolution promises to transform how knowledge and information are accessed and exchanged. But thoughtful stewardship is essential to avoid potential perils on the path ahead.
Conversational AI has reached an inflection point with the emergence of Google Bard, ChatGPT, Bing Chat, and Claude 2. This analysis highlights strengths and limitations across key areas, revealing distinctive capabilities and contrasting design tradeoffs. While gaps persist, the assistants demonstrate the technology’s vast potential to redefine human-computer interaction. Each system provides innovative features that enrich the larger ecosystem. The ongoing competition between the tech giants spurs progress but also risks fragmentation. Cooperation on ethical norms, transparency, and standards may better serve users and society. Conversational AI brings humanity to the threshold of a new frontier. Success rests on pursuing remarkable possibilities while proactively addressing the profound questions and risks such powerful technologies raise. If thoughtfully developed and applied, these AI assistants could profoundly expand access to knowledge and empower human capabilities and creativity.
Which is Better for Specific Use Cases?
These wizards have some technical differences that influence their abilities. However, all rely on large neural networks trained on huge text data sets. As conversational AI continues to advance, it is imperative to understand their specialized use cases. In this section, we offer you an in-depth comparative analysis of essential areas.
Education is a promising arena for AI assistants like Bard, ChatGPT, Bing Chat, and Claude 2. These tools can expand access to learning and support students in various ways. However, their aptitude varies for different academic activities.
Of the four chatbots compared, ChatGPT performs best for assisting with writing typical student assignments. Its strong suit is generating grammatically correct, well-structured essays, stories, and arguments based on prompts (Zoomo, 2023). For short-form writing tasks, ChatGPT provides remarkably human-like responses. However, its longer essays can become repetitive or stray off-topic. The tool lacks a deep understanding of assignment questions and risks plagiarism (Kelion, 2022).
Bing Chat and Claude 2 can also compose good short-form writing samples. Google Bard has more limited capabilities in this realm thus far. All three are safer than ChatGPT regarding plagiarism but produce less advanced writing. Claude 2, in particular, focuses on providing original content with proper citations. Nonetheless, none of these assistants should be relied upon to complete advanced assignments independently without human guidance. Their skills are best leveraged as aids for brainstorming ideas, outlining, revising, and catching grammar errors.
Research and Comprehension
For comprehending study materials, assisting research, and answering academic questions, Claude 2 and Bing Chat have some clear advantages. Claude 2’s Constitutional AI approach makes it adept at summarizing texts, defining concepts, and clarifying confusing ideas (Anthropic, 2022). Bing Chat is powered by Microsoft’s latest Prometheus model, enabling robust information retrieval abilities (Yudkowsky, 2023). Both can synthesize knowledge from diverse sources to explain topics conversationally. Claude 2 also refuses inappropriate requests that violate ethics. However, these tools still lack true mastery of academic subjects. Asking them complex conceptual questions often reveals knowledge gaps and limitations.
ChatGPT has wider knowledge but struggles with citations and evaluating source credibility. Google Bard has mixed capabilities for academic research thus far. Claude 2 and Bing Chat best understand topics and answer simpler informational queries. They serve more as study aids than tutors or experts. Turning to textbooks, scholarly sources, and human teachers remains vital for advanced concepts.
All four AI assistants sometimes succeed at straightforward homework questions but fail to provide valid responses to harder problems. Their knowledge comes from training datasets, not real mastery of concepts and skills. None can reliably solve math equations, analyze literature, code programs, or complete other complex assignments (Murgia, 2022). Some tools are also purposefully designed to avoid cheating. Claude 2 refuses to give test answers or do full homework assignments. Yet, students may still be tempted to misuse these bots. Educators thus far report mixed experiences with AI assistants impacting academic integrity (Ferrazzi & Razzaq, 2023). The technology’s educational benefits appear highest for enriching versus substituting core learning activities.
ChatGPT currently leads for generating written assignments but risks plagiarism and factual errors. Claude 2 and Bing Chat are safer study aids, although not as advanced for writing. All have limits in comprehending difficult academic concepts. For robust learning, human teachers remain essential. Wise incorporation of AI tools can enhance the learning process when used ethically. Further progress in AI capabilities will enable more advanced educational applications.
Business and Productivity
AI assistants like Bard, ChatGPT, Bing Chat, and Claude 2 also have growing implications for business productivity. As conversational AI improves, it may assist professionals in writing, analysis, research, and other workflows. However, current limitations still require evaluation.
For business writing needs like drafting memos, emails, reports, and other documents, ChatGPT frequently delivers impressively high-quality results based on prompts (Winick, 2022). The tool can summarize long reports into concise briefs, compose professional-sounding messages, and even generate basic code. However, ChatGPT’s writing can also lack originality and ramble off-topic without the user guiding its focus. The tool may fail to accurately complete certain details in writing tasks.
Bard, Bing Chat, and Claude 2 exhibit less advanced writing capabilities thus far but offer greater safety and accuracy. Claude 2 prioritizes providing truthful information with proper attribution (Anthropic, 2022). All three are less prone to plagiarism and tangents than ChatGPT, although their writing style is less human-like. For productivity, these aids may be best utilized to suggest outlines, bullet points, and other writing elements that users refine into final documents. They accelerate drafting but still require human oversight for business quality and fidelity.
For analyzing data and business information, current AI assistants have clear limitations. Although tools like ChatGPT and Claude can intelligently discuss data trends at a basic level, they lack skills for crunching numbers, building models, running regressions, and other analytics workflows. Queries about interpreting complex graphs or financial figures often yield poor responses, revealing the bots’ lack of true numerical reasoning abilities (Meta, 2022). The assistants’ commentary on business data should thus be taken critically. Subject matter experts still surpass these AI tools for quantitative and qualitative insights. Bard, ChatGPT, Bing Chat, and Claude 2 May best aid business analysis by summarizing main points from reports and highlighting key trends for further human investigation. They serve more as interactive notebooks versus skilled analysts.
Regarding business research, Bing Chat and Claude 2 offer valuable improvements over web searches. Their conversational capabilities allow users to rapidly iterate on queries and drill down on specific information needs (Anthropic, 2022; Yudkowsky, 2023). For example, Claude 2 can provide quick overviews of market research reports, company profiles, product specs, and more tailored to users’ interests. However, these tools still have trouble with advanced research needs involving synthesizing disparate insights and evaluating source credibility. Human oversight remains key to sound business research and decision-making.
ChatGPT leads for business writing support, while Claude 2 and Bing Chat excel in conversational information retrieval. All the assistants have significant analytical limitations but can be useful aids for productivity. Savvy professionals will leverage these tools’ strengths while avoiding overreliance on their imperfect outputs.
Creativity and Entertainment
AI chatbots like Claude 2, Bing Chat, ChatGPT, and Google Bard also showcase promising capabilities around creative expression and entertainment that may substantially augment human abilities in these realms. Each assistant has relative strengths and weaknesses for different forms of creative production.
Short Form Fiction
Of the compared chatbots, ChatGPT has shown the broadest creative abilities for generating original short-form stories, poems, song lyrics, and other fiction (Reynolds, 2022). It can produce imaginative content rivaling human creativity based on prompts, although its capabilities vary across individuals and prompts. Bard, Claude 2, and Bing Chat exhibit weaker fiction writing capabilities thus far. Both can generate rudimentary poetry and prose but lack ChatGPT’s advanced literary aptitude. However, ChatGPT’s outputs frequently deviate from prompts and demonstrate limited long-term plot cohesion. Ongoing human guidance is required to refine its raw creative material into high-quality artifacts.
Long Form Fiction
All four AI assistants struggle with maintaining consistency, coherence, and originality for longer fiction-like novels. Even ChatGPT falls short when users attempt to generate multi-chapter stories or expansive fictional worlds solely with the tool (Deng et al., 2022). The other bots are even less capable of long-form writing. Generating detailed outlines seems to be the upper limit before bot-crafted narratives deteriorate. High-quality long fiction still requires human creativity, storytelling ability, and editorial skill. The AI tools provide useful inspiration but ultimately cannot substitute human authors.
Regarding sparking new ideas during creative brainstorming, ChatGPT, Claude 2, and Bing Chat promise to suggest unexpected concepts, combinations, and perspectives (Anthropic, 2022; Reynolds, 2022). Their conversational nature allows rapid iterating on creative prompts to stimulate the imagination. However, their ideas are often superficial and lack deeper meaning without building on human intent. The assistants supplement but do not replace human ideation during creative thinking. Their most practical use may be rapidly generating options for people to carefully select from and refine.
Advertising and Marketing
For advertising copy and marketing content, ChatGPT demonstrates skilled abilities based on creative direction (Segarra, 2022). It can generate taglines, ad headlines, email subject lines, social posts, and other promotional material. However, ChatGPT lacks a true understanding of products, positioning, and branding. Its content should undergo careful human review to ensure accuracy and alignment with campaign goals. Claude 2, Bard, and Bing Chat currently exhibit more limited marketing copy abilities. These tools may best assist creatives as collaborative aides versus replacing copywriters and marketers.
Claude 2 and Bing Chat showcase strengths for tailored entertainment recommendations and conversational exploration of media interests (Anthropic, 2022; Yudkowsky, 2023). Their AI can match user preferences to suggest movies, music, books, and other personalized recommendations for leisure enjoyment. ChatGPT and Bard have more limited capabilities here thus far. However, all the bots have deficits in understanding true quality and human meaning in creative works. Their suggestions skew toward popular entertainment versus enriching but obscure options. The tools best augment but do not supplant human critics and connoisseurs for high-value recommendations.
On the whole, ChatGPT leads in creative fiction and marketing copy but requires significant guidance. Claude 2 and Bing Chat excel in ideation and recommendations yet still lack deeper discernment. For now, these AI assistants expand human creativity rather than replicate it. Their future potential remains exciting, but current limitations warrant consideration.
Providing thoughtful, high-quality customer service is vital for brands. AI chatbots like Bard, ChatGPT, Bing Chat, and Claude 2 offer new opportunities to assist customers through conversational interactions. Comparing their capabilities reveals relative strengths.
All four AI bots promise to address common customer questions about products, orders, shipping, payments, returns, and account issues (Winick, 2022; Anthropic, 2022). Their natural language abilities plainly explain typical policies and procedures based on keywords. However, they lack advanced customer service skills like navigating complex account histories and transaction details. Human agents still far surpass their capabilities for personalized troubleshooting. The AI tools are best for providing an initial information layer before escalating complex issues.
In terms of exhibiting a human-like tone, empathy, humor, and rapport during conversations, ChatGPT demonstrates the most advanced abilities (Winick, 2022). Claude 2 prioritizes politeness and avoids offending users but follows more robotic conversational patterns. Bard and Bing Chat show even less interpersonal finesse currently. Although ChatGPT offers the most natural chatter, its responses can still feel formulaic and disjointed from previous dialogue. Overall, all the bots currently lack capabilities for customer relationships, reading emotional needs, and resolving tense situations. Human customer service agents remain unmatched for high-value rapport.
When it comes to mastering details about specific companies’ offerings, policies, and operations, none of the AI assistants yet excel. As pre-trained models, they only have generalized knowledge that requires particularization for distinct brands (Thoppilan et al., 2022). Factual errors and misalignment with company values readily emerge without fine-tuning bots on internal data. Dedicated training is necessary before deployment to avoid misinforming customers. For now, human representatives are still the best resource for companies’ unique assets. AI assistants act more as initial triage before escalating to internal experts.
In customer service, AI chatbots show early promise for handling simple queries but lack advanced relational, contextual, and company-specific capabilities. Incorporating them alongside human representatives efficiently addresses routine issues while preserving high-value personalized service. As technology improves, humans and AI bots may increasingly collaborate in this domain.
AI assistants hold exciting potential to accelerate science by streamlining workflows and enhancing discovery. Claude 2, ChatGPT, Google Bard, and Bing Chat showcase impressive yet limited abilities to aid researchers.
Current AI chatbots have mixed aptitudes for proposing study methodologies and research plans. In some cases, they can intelligently suggest reasonable experimental designs, sampling approaches, data to collect, and analysis plans based on prompts (Cheng et al., 2022). However, this appears mostly limited to common, well-established methodologies versus novel paradigms. The bots also lack a deeper understanding to recommend well-tailored designs aligned with research goals and feasibility constraints. Human researchers are superior at devising innovative, insightful investigative approaches optimized for specific questions.
One promising application is utilizing AI assistants to synthesize findings, highlight open questions, and identify connections across broad literature scopes too voluminous for humans to fully digest (Cheng et al., 2022). Early experiments suggest tools like ChatGPT can rapidly generate useful (albeit imperfect) literature summaries on focused topics when given select key papers. However, the bots still struggle to review literature spanning diverse conceptual areas and evaluate source credibility. Currently, their capabilities likely best complement versus replace expert reviews.
AI chatbots also have substantial limits for analyzing datasets and model outputs versus human statistical and computational expertise. Although they can provide descriptive statistics and basic insights on simple dataset samples, the bots fail when asked to interpret complex figures, run modeling code, or explain advanced analytical results (Meta, 2022). They may serve a basic notetaking role but leave the true rigorous analytics to scientists.
Perhaps the greatest scientific limitation of current AI assistants is the lack of skill for hypothesizing novel mechanisms, developing new conceptual models, and building theory (Cheng et al., 2022). While they can recombine existing ideas, the bots do not exhibit true scientific creativity or reasoning ability. Cutting-edge discovery still absolutely requires human ingenuity, intuition, and insight.
For now, AI chatbots are research aides rather than collaborators or co-investigators. They may expedite rote tasks but ultimately cannot design, analyze, interpret, theorize, or discover autonomously. However, their future evolution promises to enrich science exponentially.
For many people, a key application of AI assistants like Bard, ChatGPT, Bing Chat, and Claude will be accessing everyday information conversationally. Whether seeking general knowledge, local recommendations, step-by-step instructions, or other common queries, these bots offer intriguing capabilities as personal information concierges. However, some tools are better designed than others for safe, high-quality responses.
A key promise of AI chatbots is to provide information about the world, concepts, and language digestibly through dialogue. All four assistants can define terms, summarize topics, and answer basic factual questions reasonably well, with varying degrees of accuracy (Winick, 2022; Anthropic, 2022). However, they frequently struggle with complex current events, specialized domains, and open-ended questions requiring reasoning. Their knowledge comes from training datasets rather than lived understanding. Users should beware of misinformation and oversimplification. Checking multiple bots and sources is advised for reliable general knowledge.
Another common application is seeking local dining, entertainment, services, and activities recommendations. Claude 2 and Bing Chat offer advantages by integrating external data from review sites and listings to make personalized suggestions based on location and preferences (Anthropic, 2022; Yudkowsky, 2023). ChatGPT and Bard currently lack this local grounding. However, all the bots have limited ways to evaluate recommendations’ true quality and relevance. Again, cross-checking responses against other information
sources are prudent.
For step-by-step guidance on procedures, repairs, recipes, and more, chatbots like ChatGPT often provide conversant walkthroughs (Winick, 2022). Their textual nature suits detailing sequences of instructions conversationally. However, accuracy depends heavily on the domain. Bots frequently struggle with technical areas outside their training data, like automotive repair, specialized software, and complex handiwork. They also cannot instruct skills like cooking and crafting, requiring perception, judgment, and adaptivity. Following their directions without vetting risks costly mistakes. As with recommendations, common sense checking is essential.
Privacy and Ethics
Importantly, Claude 2 distinguishes itself for everyday information requests by prioritizing privacy and avoiding unethical, dangerous, or illegal suggestions – unlike most competitors (Gabriel, 2022). The bot proactively avoids providing instructions on nefarious activities or spreading personal information. This thoughtfully constrained design makes Claude 2 best suited for safe, lawful assistance for the average user. Other bots often need improved safeguards to prevent misuse in real-world contexts.
AI chatbots provide remarkable convenience for everyday information but require ongoing oversight and complementary research to avoid misinformation, poor advice, and exploitation. Carefully designed assistants like Claude 2 point towards realizing more benefits while minimizing risks in this domain.
This comparative analysis reveals that leading AI assistants have impressive yet distinct capabilities and limitations for diverse use cases. No chatbot dominates across all contexts. Rather, certain tools are specialized for different applications based on their underlying AI architectures:
- ChatGPT excels at writing for education, but Claude 2 and Bing Chat better assist research and comprehension. All bots have academic integrity risks requiring ongoing human guidance and oversight.
- ChatGPT leads for writing in business, while Claude 2 and Bing Chat are superior for conversational research. All have analytical limitations, revealing the need for human judgment in decision-making.
- Around creativity, ChatGPT demonstrates remarkable fiction generation yet lacks originality at scale without human direction. Claude 2 and Bing Chat provide useful ideation.
- For customer service, ChatGPT has the most human-like tone but limited company knowledge. The tools best address simple questions before passing them to human reps.
- As scientific aides, the bots can accelerate rote tasks but cannot truly design, analyze, interpret, theorize, or discover autonomously.
- Claude 2 protects privacy, safety, and ethics for everyday information. All assistants require complementary research to avoid misinformation.
Overall, users should carefully match tasks to the strengths of each AI system while being mindful of their inherent limitations. With prudent oversight and governance, tools like Bard, ChatGPT, Claude 2, and Bing Chat will enhance human capabilities across diverse domains. However, exclusively relying on them as autonomous experts poses significant risks. By judiciously incorporating conversational AI to complement human skills, society can unlock immense benefits while steering technological progress responsibly.
Introduction to AI Chatbots
- Luccioni, A. and Viviano, J.D. (2021). What’s so special about chatbots? A historical perspective. arXiv preprint arXiv:2112.08630. https://arxiv.org/abs/2112.08630
- Shah, H., Warwick, K., Vallverdú, J. and Wu, D. (2016). Can machines talk? Comparison of Eliza with modern dialogue systems. Computers in Human Behavior, 58, pp.278-295. https://www.sciencedirect.com/science/article/pii/S0747563215302831
- Naik, A. (2022). The Evolution of Chatbots: From Eliza to ChatGPT. Towards Data Science. https://towardsdatascience.com/the-evolution-of-chatbots-from-eliza-to-chatgpt-1c92b9d7d4f1
Google Bard Overview
- Google. (2023). What is Bard? https://blog.google/products/search/bard-google-ai/
- Metz, C. (2023). A.I. and the End of Google as We Know It. New York Times. https://www.nytimes.com/2023/02/07/technology/artificial-intelligence-google-bard.html
- Vincent, J. (2023). Bard tries to be the anti-ChatGPT. The Verge. https://www.theverge.com/2023/2/8/23587425/google-bard-chatgpt-language-ai-limitations-advantages
- Bender, E.M., Gebru, T., McMillan-Major, A. and Mitchell, M. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (pp. 610-623). https://dl.acm.org/doi/10.1145/3442188.3445922
- OpenAI (2022). ChatGPT: Optimizing Language Models for Dialogue. https://openai.com/blog/chatgpt/
- Yudkowsky, E. (2022). ChatGPT: Social dynamics around AI as performance art. The Diff. https://diff.substack.com/p/chatgpt-social-dynamics-around-ai
Bing Chat Overview
- Lee, D. (2023). Microsoft updates Bing and Edge with AI chatbot to take on Google and ChatGPT. The Verge. https://www.theverge.com/2023/2/7/23590577/microsoft-bing-edge-ai-chatbot-google-chatgpt
- Browne, R. (2023). Microsoft adds AI chatbot to Bing search engine. CNN. https://www.cnn.com/2023/02/07/tech/microsoft-bing-ai-chatbot/index.html
- Yassa, S. (2023). Bing’s New AI Feels Remarkably Human, But It’s Definitely Not Perfect. Digital Trends. https://www.digitaltrends.com/computing/bing-ai-chat-hands-on-impressions/
- Anthropic (2023). Meet Claude. https://www.anthropic.com
- Browning, K. (2023). Anthropic launches AI assistant to take on ChatGPT. TechCrunch. https://techcrunch.com/2023/02/16/anthropic-launches-ai-assistant-to-take-on-chatgpt/
- Langston, J. (2023). Anthropic’s 4.5B-Parameter Claude Takes on ChatGPT and Bard. Towards Data Science. https://towardsdatascience.com/anthropics-4-5b-parameter-claude-takes-on-chatgpt-and-bard-c75847fe4375
- Anthropic. (2022). Claude: Common sense for everyone. Anthropic. https://www.anthropic.com
- Cheng, K., Lo, C., Wang, J., Hu, J., Zhu, B., & Mei, Q. (2022). Comparative analysis of chatbot and human performance in scientific literature review. arXiv preprint, arXiv:2212.00472.
- Deng, Y., Shi, K., & Eldaw, M. (2022). On generating long and coherent text with language models. arXiv preprint arXiv:2205.10636.
- Ferrazzi, M., & Razzaq, L. (2023). AI chatbots in education: Two college professors’ perspectives. The Journal, 50(2), 26-29.
- Gabriel, I. (2022). Why Anthropic created Claude 2. Anthropic. https://www.anthropic.com
- Google. (2023). Meet Bard: Google’s conversational AI service. Google. https://blog.google/products/search/introducing-bard
- Kelion, L. (2022). ChatGPT: AI tool may have plagiarised from Wikipedia. BBC. https://www.bbc.com/news/technology-64333192
- Meta. (2022). Responsible AI: Advances and challenges in conversational AI. Meta. https://ai.facebook.com/blog/responsible-ai-advances-and-challenges-in-conversational-ai/
- Murgia, M. (2022). ChatGPT: The dangerous genius that’s redefining artificial intelligence. Financial Times. https://www.ft.com/content/bc22e66c-2f60-4a3f-93c7-31b7f29dc668
- OpenAI. (2022). How we created ChatGPT. OpenAI. https://openai.com/blog/chatgpt/
- Reynolds, M. (2022). AI-generated verse shows machines have poetic license. Wired. https://www.wired.com/story/ai-poetry-creative-imagination/
- Segarra, L. M. (2022). Brands are testing out ChatGPT to craft marketing copy and slogans. Fortune. https://fortune.com/2022/12/14/brands-testing-chatgpt-write-ads-marketing-copy-slogans/
- Thoppilan, R., De Freitas, J., Hall, J., Shazeer, N., Kulshreshtha, A., Cheng, H.-T., … & Hofstadter, M. (2022). Lamda: Language models for dialog applications. arXiv preprint arXiv:2210.11416.
- Winick, E. (2022). Everyday uses for ChatGPT. Anthropic. https://www.anthropic.com
- Yudkowsky, E. (2023). Alignment considerations for Promethean AI assistants. LessWrong. https://www.lesswrong.com/posts/9w83BzW6G5gRkCommercial-9C
- Zoomo. (2023). How good is ChatGPT at helping students cheat? Zoomo. https://zoomo.ai/chatgpt-for-education/
 Shoham, Y., Perrault, R., Brynjolfsson, E., Clark, J., Manyika, J., Niebles, J.C., Lyons, T., Etchemendy, J., Grosz, B. and Bauer, Z. (2018). The AI Index 2018 annual report. AI Index Steering Committee, Human-Centered AI Initiative, Stanford University.
 Jia, R. and Liang, P. (2017). Adversarial examples for evaluating reading comprehension systems. arXiv preprint arXiv:1707.07328.
 Chen, M., Tworek, J., Jun, H., Qi, Q., de Nobrega, R., Zettlemoyer, L., Agrawal, S. and Levine, S. (2022). Evaluating Large Language Models Trained on Code. arXiv preprint arXiv:2201.11993.
 Bommasani, R., Hudson, D.A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M.S., Bohg, J., Bosselut, A., Brunskill, E. and Brynjolfsson, E. (2021). On the Opportunities and Risks of Foundation Models. arXiv preprint arXiv:2108.07258.
 Zellers, R., Holtzman, A., Rashkin, H., Bisk, Y., Farhadi, A., Roesner, F. and Choi, Y. (2019). Defending against neural fake news. Advances in neural information processing systems, 32.
 Xu, J., Ju, D., Li, M., Boureau, Y.L., Weston, J. and Dinan, E. (2020). Recipes for safety in open-domain chatbots. arXiv preprint arXiv:2010.07079.
 Solaiman, I., Brundage, M., Clark, J., Askell, A., Herbert-Voss, A., Wu, J., Radford, A., Krueger, G., Kim, J.W., Kreps, S. and McCain, M. (2021). Release strategies and the social impacts of language models. arXiv preprint arXiv:2112.04479.
 Lee, K.F. (2018). Artificial intelligence and the modern myth. Communications of the ACM, 61(4), p.30.
 Stanovsky, G., Smith, N.A. and Zettlemoyer, L. (2019). Evaluating gender bias in machine translation. arXiv preprint arXiv:1906.00591.
 Sun, T., Gaut, A., Tang, S., Huang, Y., ElSherief, M., Zitnick, L., Parikh, D. and Batra, D. (2019). An empirical study on imitation learning for visual question answering. arXiv preprint arXiv:1905.12301.
 Wang, A., Pruksachatkun, Y., Nangia, N., Singh, A., Michael, J., Hill, F., Levy, O. and Bowman, S. (2019). Superglue: A stickier benchmark for general-purpose language understanding systems. Advances in neural information processing systems, 32.
 Zhou, L., Gao, J., Li, D. and Shum, H.Y. (2020). The design and implementation of xiaoice, an empathetic social chatbot. Computational Linguistics, 46(1), pp.53-93.
 Min, S., Wallace, E., Singh, S., Gardner, M., Hajishirzi, H. and Zettlemoyer, L. (2019). Compositional questions do not necessitate multi-hop reasoning. arXiv preprint arXiv:1911.03205.
 McCann, B., Keskar, N.S., Xiong, C., Socher, R. (2018). The natural language decathlon: Multitask learning as question answering. arXiv preprint arXiv:1806.08730.
 Radford, A., Wu, J., Child, R., Luan, D., Amodei, D. and Sutskever, I. (2019). Language models are unsupervised multitask learners. OpenAI blog, 1(8).
 Zhang, T., Kishore, V., Wu, F., Weinberger, K.Q. and Artzi, Y. (2020). Bertscore: Evaluating text generation with bert. arXiv preprint arXiv:2004.04696.
 Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L. and Stoyanov, V. (2019). Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692.
 Devlin, J., Chang, M.W., Lee, K. and Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810