👊😎 ‘Just Take the Whole Market’

PLUS: The Curious Case of LaMDA

In today’s Tracker:

Read time: 3 mins

  • 🧪 Research highlights: The Dark Side of ChatGPT: Unreliable Sourcing Issues Uncovered

  • 🚨 Industry news: Palantir's Bold Plan to Dominate AI Market Sends Investors Wild

  • ⚖️ Policy and regulation: German Ruling Party Takes Aim at AI Bias with New Digital Policy Paper

  • 🌐 AI and society: The Philosophy of AI Needs a More Precise Vocabulary to Navigate Reality

  • 🧰 Tool of the day: AutoBackend: The Automated Solution to Backend Woes

  • 🧠 Let’s get smart with AI: The Secret Ingredient to Neural Networks: Understanding Activation Functions

🚩 The Dark Side of ChatGPT: Unreliable Sourcing Issues Uncovered

A study by the Human-Centered AI research group at Stanford University found that generative search engines, including those that fuel AI chatbots like ChatGPT, have accuracy issues due to unreliable sourcing.

The study examined four prominent search engines, focusing on four characteristics: fluency, perceived utility, citation recall, and citation precision.

According to the researchers, only about half of generated sentences were thoroughly supported by citations and one-fourth of citations needed to have supported associated sentences.

They concluded that the illusion of reliability established by these systems increases their capacity to mislead users. The researchers believe their findings will encourage the creation of more reliable generative search engines.

💪 Palantir's Bold Plan to Dominate AI Market Sends Investors Wild

Palantir's CEO, Alex Karp, has stated that the company plans to dominate the entire artificial intelligence (AI) market.

The announcement has sparked investor optimism, with shares in the data analysis firm rising 23%.

With no pricing strategy, the company plans to roll out the first version of its AI Platform, or AIP, to select customers over the coming weeks.

Karp has suggested that "when you're ahead of the market, you must take territory." Palantir's core pitch is its ability to handle sensitive AI tools, as demonstrated by its long experience with classified networks.

🌐 German Ruling Party Takes Aim at AI Bias with New Digital Policy Paper

Saskia Esken, the leader of Germany's ruling party, has called for scrutiny of the discriminatory aspects of data sets used to train AI models.

Esken suggested that AI tools could display bias against groups such as women seeking jobs as IT specialists or young men applying for credit checks if data sets were not "cleaned up."

She was presenting the Social Democrat's new digital policy paper, which also calls for transparency and responsibility in developing and deploying AI models.

The paper also advocates for a four-day workweek to enable a more excellent work-life balance.

📘 The Philosophy of AI Needs a More Precise Vocabulary to Navigate Reality

A Google engineer's belief that the chatbot LaMDA, based on a Large Language Model (LLM), is conscious, sentient, and a person has sparked debate over the definitions of intelligence, sentience, and consciousness.

While the controversy is based on motivated anthropomorphic projection, AI can be intelligent or conscious in specific ways, depending on how these terms are defined.

A more precise vocabulary is needed to name and measure what is already here and orient what is to come.

The philosophy of AI and AI research have deeply intertwined histories, and a more creative approach is needed to parse the current reality.

💻 AutoBackend: The Automated Solution to Backend Woes

Autobackend, an AI tool, automates the backend development process. Its goal is to generate high-quality backend code, saving developers time and effort.

Learn more about the tool here.

🧮 The Secret Ingredient to Neural Networks: Understanding Activation Functions

An activation function in AI is a mathematical function applied to each neuron's output in a neural network.

The purpose of the activation function is to introduce non-linearity into the output of the neuron, allowing the neural network to learn complex patterns and relationships in the data.

Without an activation function, a neural network would be limited to learning only linear relationships, severely restricting its capabilities.

Different activation functions are used in neural networks, including sigmoid, ReLU (rectified linear unit), and tanh (hyperbolic tangent) functions, each with advantages and limitations.

—Kathy Baxter, ethical AI practice architect, Salesforce

The three big categories [for building ethics into AI] are creating an ethical culture; then being transparent, and finally, removing the exclusion, whether that’s in your data sets or your algorithms.

—Stephen Covey

Live out of your imagination, not your history.

r/singularity, u/LevelWriting

Credit: walkingtalkk

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