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News Roundup
AI May Enable Interstellar Communication - By transmitting a well-curated LLM to extraterrestrial civilizations, we could enable them to converse with us indirectly.
Top Tech Giants Unite to Create AI Security Standards - The Coalition For Secure AI, announced by Google during the Aspen Security Forum, will focus on establishing industry-wide standards and best practices for AI security
DeepL’s Next-Gen Language Translation - In blind tests, language experts prefer DeepL’s translations 1.3x more often than Google Translate, 1.7x more than ChatGPT-4, and 2.3x more than Microsoft.
Qualcomm Hopes to Boost AI App Development - Qualcomm makes its AI models available to app developers, empowering them to create AI-enabled applications that harness the capabilities of the company’s powerful Hexagon neural processing unit.
Todays Top Story
Mistral AI has released Mathstral, a finetuned 7B model designed for math reasoning and scientific discovery, offering a 32k context window and openly available model weights.
The model’s release comes amidst questions about leading LLMs’ ability to solve complex math problems while lacking an understanding of elementary school math concepts in certain cases.
Mathstral demonstrates the trend of fine tuned open source models outperforming larger closed source models in specialized areas. The model successfully answers questions like comparing the value of 9.11 and 9.9, providing correct reasoning and demonstrating its understanding of basic math concepts more broadly.
AI and Human Thought Pt. 2
AI's increasing omnipresence will fundamentally alter human thought and daily experiences, emphasizing the crucial importance of AI literacy.
AI is no stranger to the digital ecosystem, having made itself at home in many different sectors long before the emergence of LLMs and other forms of advanced AI. Google began integrating machine learning features into its search engine as early as 2001, Facebook has been leveraging AI since its inception in 2006, and Amazon claims that its use and development of AI spans over two decades.
Looking back on the history of AI, a clear trend emerges: AI proved most valuable either in situations where lots of data needed to be quickly and accurately classified, synthesized, and interpreted or in cases where humans were required to perform undesirable, dangerous, or time-consuming tasks.
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