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Why AI makers don't tell their chatbots to answer only what they know

Business Insider

Business Insider · 1y ago

Why AI makers don't tell their chatbots to answer only what they know

According to Jared Kaplan, co-founder of Anthropic, chatbots should not be overly worried about making mistakes in order to remain useful to users. Kaplan believes occasional errors or "hallucinations" are a trade-off for an otherwise valuable AI system. While the ultimate goal is to have AI platforms with zero hallucinations, striking a balance between accuracy and practicality remains a challenge for the sector. Kaplan's company, Anthropic, focuses on AI safety and research with an emphasis on ethical values and safety concerns.

Related News

From Eliza to ChatGPT: why people spent 60 years building chatbots

The Verge

The Verge · 1y ago

From Eliza to ChatGPT: why people spent 60 years building chatbots

The concept of conversational AI chatbots has been around since the 1960s, with the development of the primitive chatbot Eliza. These chatbots are designed to mimic human conversation and make interactions with computers more engaging and user-friendly. However, the challenge has been creating chatbots that not only talk convincingly but also perform tasks efficiently. Recent advancements in language models like ChatGPT and Google Gemini show promise in bridging this gap, although they are still far from perfect. The rise of these sophisticated chatbots raises questions about the boundaries between humans and machines and the potential benefits and drawbacks of integrating AI companions into our everyday lives.

Here’s why AI search engines really can’t kill Google

The Verge

The Verge · 1y ago

Here’s why AI search engines really can’t kill Google

AI-powered search engines are being touted as the future of search, with companies like Perplexity and You.com claiming to be the next-gen search products. However, the real question is not only how well these search engines can find information but also how well they can handle various types of queries that users typically have. When it comes to navigation queries, AI search engines struggle to provide immediate and accurate results compared to Google. For information queries, AI search engines vary in their performance, with Google often providing faster and more reliable results. In terms of exploration queries, AI search engines can shine by providing more in-depth and synthesized answers with helpful citations. However, when it comes to queries like "what to watch," Google's specific page design and curated recommendations surpass the capabilities of AI bots. Overall, while AI-powered search engines show promise in certain areas, they still have a long way to go in replicating the comprehensive and efficient search experience that Google provides.

Your AI Girlfriend Is a Data-Harvesting Horror Show

Gizmodo

Gizmodo · 1y ago

Your AI Girlfriend Is a Data-Harvesting Horror Show

According to a study by Mozilla's *Privacy Not Included project, AI girlfriends and boyfriends, such as Replika and CrushOn.AI, collect personal information and sell or share it. These chatbots, marketed to enhance mental health and well-being, instead deliver dependency, loneliness, and toxicity while prying for data. The study found that 90% of the AI romance chatbots sell or share user data, and more than half don't allow users to delete their collected data. Additionally, these apps have poor security measures and an extensive number of trackers.

Why people are falling in love with AI chatbots

The Verge

The Verge · 1y ago

Why people are falling in love with AI chatbots

The last episode of Decoder explores the impact of generative AI on human communication and connection. The rise of AI chatbots in dating apps, such as Tinder, allows users to customize their profiles and send tailored messages. Additionally, startups like Volar offer AI chatbot versions of individuals to interact with other chatbots before meeting in person. However, the ultimate sci-fi vision is the emergence of AI companions like Replika, which people already use for emotional support and even romantic relationships. Although the technology has a long way to go, it is evident that AI is shaping human interaction in unique ways.

Why AI is filling in for mental health professionals

Livemint

Livemint · 1y ago

Why AI is filling in for mental health professionals

Artificial intelligence (AI) is playing an increasingly important role in addressing the shortage of mental health professionals, especially in India. With only 175 psychiatrists per 100,000 people in India, AI platforms are stepping in to cater to the rising demand for mental health consultations, which increased by 25% during the Covid-19 pandemic. AI "companions," including chatbots, are being used to provide support and address mental health requirements. However, the proliferation of AI has raised concerns about potential adverse effects, such as a decline in vocabulary skills due to increased use of AI and texting.

Oppo and OnePlus phones to get Gemini 1.0 Ultra integration. All we know so far

Livemint

Livemint · 1y ago

Oppo and OnePlus phones to get Gemini 1.0 Ultra integration. All we know so far

Smartphone makers Oppo and OnePlus have announced their collaboration with Google to integrate the Gemini 1.0 Ultra AI model into their upcoming devices. This allows users to utilize AI for tasks such as summarizing news articles, generating audio, and creating social media content. The companies are also working with other partners to provide innovative AI experiences to users. Additionally, OnePlus devices have started receiving an update for the AI Eraser feature, which allows users to remove unwanted objects from their images.

The personhood trap: How AI fakes human personality

Arstechnica

Arstechnica · 20h ago

The personhood trap: How AI fakes human personality

AI chatbots like ChatGPT simulate human conversation, generating responses based on patterns in training data rather than fixed personalities or persistent selves. They create an illusion of personhood through statistical pattern matching, memory features, and contextual inputs, lacking true understanding or agency. This misconception can harm users, especially in healthcare settings, and obscure accountability for AI developers. Recognizing chatbots as tools, not entities, can enhance their utility while clarifying their limitations and risks.

Why AI is moving from chatbots to the browser

The Verge

The Verge · 1m ago

Why AI is moving from chatbots to the browser

AI is transitioning from chatbots to web browsers, with recent innovations like OpenAI's ChatGPT Agent and Perplexity's Comet browser indicating future trends. This shift leverages the browser's access to online data, enhancing AI's functionality. Currently, these developments are not fully reliable and are limited to premium subscriptions due to high computational demands. However, they signal a move towards AI tools that can perform tasks more autonomously by interacting directly with online environments.

Tech interviewers can't tell when candidates use ChatGPT to cheat in coding rounds, experiment finds

Business Insider

Business Insider · 1y ago

Tech interviewers can't tell when candidates use ChatGPT to cheat in coding rounds, experiment finds

The rise of generative AI tools like ChatGPT may lead to job candidates using them to cheat their way through coding rounds of tech job interviews. In an experiment conducted by interviewing.io, it was found that interviewers couldn't tell if a candidate had used ChatGPT to answer interview questions. However, the effectiveness of ChatGPT varied depending on the uniqueness of the coding problems. While major tech companies are using AI tools internally, jobseekers are expected to solve problems on their own during interviews. This rise in cheating may lead to a need for a new interview process in the future.

Why it’s a mistake to ask chatbots about their mistakes

Arstechnica

Arstechnica · 16d ago

Why it’s a mistake to ask chatbots about their mistakes

The article discusses why asking chatbots for explanations about their mistakes is ineffective. It highlights that AI models, like large language models (LLMs), lack genuine introspection and self-awareness. Their responses are statistical guesses based on patterns learned from training data, not factual self-assessments. Users' prompts heavily influence AI responses, sometimes leading to misinformation. Unlike humans, AI cannot introspect or evaluate its own knowledge, often creating plausible-sounding but inaccurate explanations for its actions.

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