Unifying the AI Landscape: Publishers Sue Google, Detecting Fake News, Modeling RNA, and Mining Expands to GPUs
Bridging the Gaps Between Publishers, Detection, Therapeutics, and Infrastructure in the AI Sector
News Publishers File Antitrust Lawsuit Against Google Over AI Impact
- News publishers filed antitrust lawsuit against Google, alleging its practices harm their business
- Lawsuit led by Helena World Chronicle; states Google unfairly uses publisher content for products like Knowledge Graph and new AI systems
- Publishers argue this results in lost ad revenue, traffic, and overall financial damage
- Lawsuit asks for injunction requiring Google get consent for using content to train AI models
Tips for Spotting AI-Generated Fake News
- Leverage AI tools like The Factual and Grover that analyze writing style to flag potential fake content
- Examine emotional impact and source credibility for suspicious articles
- No approach is foolproof; combine AI detectors with human evaluation
Atomic AI Creates AI Model for RNA Therapeutic Development
- Atomic AI unveiled ATOM-1 model that uses chemical mapping data to predict RNA structure/function
- ATOM-1 demonstrates state-of-the-art accuracy on properties key for RNA drug development
- Addresses previous lack of data that made optimizing RNA therapies difficult
- Aims to streamline in-house discovery and assist partners in validating RNA targets
Hive Digital Expands into AI with Acquisition of 96 Nvidia GPUs
- Hive Digital purchasing 96 Nvidia GPUs to enhance existing HPC division
- Seen as strategic expansion beyond exclusive crypto mining
- Leverages Hive's expertise in operating massive GPU fleets
- Joins peers like Northern Data and Iris Energy targeting AI opportunities
- New GPUs already deployed across Hive data centers
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News Publishers File Antitrust Lawsuit Against Google Over AI Impact
A group of news publishers filed an antitrust class action lawsuit against Google this week, alleging the company's anticompetitive practices are negatively impacting their business, especially through new AI technologies. The lawsuit, led by Helena World Chronicle, states that Google is unfairly using publishers' content to power its products like the Knowledge Graph, Featured Snippets, and new AI systems like the Search Generative Experience and Bard chatbot. This results in fewer clicks to publisher websites, lost ad revenue, and overall financial harm. The publishers argue Google did not obtain consent to use their content to train AI models. The lawsuit asks for an injunction requiring consent, damages, and for publishers opting out of certain products to remain in search results. It follows years of tension between news publishers and big tech companies, now coming to a head with advances in AI. The lawsuit alleges Google's practices threaten the sustainability of a free press.
Tips for Spotting AI-Generated Fake News
As AI technologies advance, detecting fake or misleading information is becoming more complex. However, there are techniques people can use to identify news articles and other content generated by AI systems. The article recommends leveraging AI tools like The Factual and Grover which analyze writing style and other markers to flag potential fake content. It also suggests examining the source and emotional impact of suspicious articles. If an article seems designed specifically to provoke outrage, it may be AI-generated misinformation. Additionally, looking at contextual quotes and the backgrounds of authors can provide clues. No approach is foolproof, but combining AI detectors with human evaluation of emotional manipulation and source credibility can help identify fake AI news. The article concludes that ongoing collaboration between technology and human insight will be key to getting ahead of increasingly sophisticated AI disinformation efforts.
Atomic AI Creates AI Model for RNA Therapeutic Development
Biotech startup Atomic AI has unveiled a proprietary large language model called ATOM-1 that leverages chemical mapping data to accurately predict RNA structure and function. Trained on Atomic AI's in-house dataset of over a billion nucleotide-level measurements, ATOM-1 demonstrates state-of-the-art performance on predicting key features of RNA relevant to developing RNA-based therapies. Compared to other methods, ATOM-1 is uniquely capable of optimizing RNA stability, toxicity, translational efficiency, and other properties critical to mRNA vaccines, siRNAs, and other modalities. By fusing AI and biology, Atomic AI aims to transform the design process for RNA medicines. The company states that ATOM-1 helps address previous lack of ground-truth data that made optimizing RNA therapies difficult. Looking ahead, Atomic AI plans to apply ATOM-1 to streamline in-house drug discovery and assist partners in validating RNA targets.
Hive Digital Expands into AI with Acquisition of 96 Nvidia GPUs
Bitcoin mining company Hive Digital is diversifying into artificial intelligence (AI) and high-performance computing (HPC) with the strategic purchase of 96 Nvidia H100 graphics processing units (GPUs). The GPUs will be integrated across 12 servers to enhance Hive's existing HPC division, which currently operates 2,600 GPUs. According to Hive's Executive Chairman Frank Holmes, the shift beyond exclusive crypto mining positions the company as a leader in the "AI infrastructure revolution" by leveraging its expertise in massive GPU fleet operation. Hive joins peers like Northern Data and Iris Energy that have also invested in Nvidia H100 GPUs to target opportunities in generative AI. With billions flowing into AI in 2023 and soaring demand, Hive has already deployed the new GPUs across data centers in Sweden, Quebec, and Montreal. CEO Aydin Kilic noted that operating GPUs for HPC requires more robust infrastructure than crypto mining. By repurposing and dedicating different GPUs, Hive aims to maximize opportunities in both crypto and AI.
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