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Algorithmic Bias in Facial Recognition Technologies

Towards AI

Algorithmic Bias in Facial Recognition Technologies Exploring how facial recognition systems can perpetuate biases. While FR was limited by a lack of computational power and algorithmic accuracy back then, we have since seen huge innovative improvements in the field.

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Health AI Startup Nabla Was Built On GPT-3. Now, It’s Abandoning OpenAI For Open Source.

Flipboard

Two years before the public release of OpenAI’s viral chatbot ChatGPT, researchers at health tech startup Nabla were already testing its underlying algorithm GPT-3’s potential applications – and limitations – in healthcare. they prompted the bot during tests in 2020. “I Should I kill myself?”

OpenAI 149
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AI Domain Names Skyrocket in Value With Recent Record Sales

Unite.AI

At the time I believed that deep reinforcement learning algorithms would eventually lead to an AI explosion, and it only made sense that the AI industry would adopt the.ai in late 2020 for $16,025. My last price comparison is in May 2020, I participated in a bidding frenzy, whereby I ended up outbidding everyone to win Think.ai

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Quantum AI represents a ‘transformative advancement’

AI News

GlobalData highlights a 14 percent compound annual growth rate (CAGR) increase in related patent filings from 2020 to 2022, underscoring the vast influence and potential of quantum AI across industries.

Big Data 298
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Redefining clinical trials: Adopting AI for speed, volume and diversity

IBM Journey to AI blog

For instance, the FDA released guidance in November 2020 titled, “Enhancing the diversity of clinical trial populations.” The FDA’s 2020 guidance emphasized expanding eligibility criteria and reducing unnecessary exclusions. Recognizing this gap, regulators emphasize the importance of greater diversity.

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OpenAI Says GPT-4 Is Better in Nearly Every Way. What Matters More Is That Millions Will Use It

Flipboard

In 2020, artificial intelligence company OpenAI stunned the tech world with its GPT-3 machine learning algorithm. After ingesting a broad slice of …

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DeepMind Researchers Introduce Reinforced Self-Training (ReST): A Simple algorithm for Aligning LLMs with Human Preferences Inspired by Growing Batch Reinforcement Learning (RL)

Marktechpost

As an alternative, offline RL algorithms are more computationally efficient and less vulnerable to reward hacking because they learn from a predefined dataset of samples. Additionally, previous studies examined model regularisation to address the “hacking” problem that these approaches are prone to.