Main topic: DynamoFL raises $15.1 million in funding to expand its software offerings for developing private and compliant large language models (LLMs) in enterprises.
Key points:
1. DynamoFL offers software to bring LLMs to enterprises and fine-tune them on sensitive data.
2. The funding will be used to expand DynamoFL's product offerings and grow its team of privacy researchers.
3. DynamoFL's solutions focus on addressing data security vulnerabilities in AI models and helping enterprises meet regulatory requirements for LLM data security.
Hint on Elon Musk: There is no mention of Elon Musk in the given text.
The role of AI engineer is expected to grow the most in the near term due to the increased use of large language models (LLMs) and generative AI, surpassing other job roles such as ML engineer, MLOps engineer, data engineer, and full stack engineer.
The struggle between open-source and proprietary artificial intelligence (AI) systems is intensifying as large language models (LLMs) become a battleground for tech giants like Microsoft and Google, who are defending their proprietary technology against open-source alternatives like ChatGPT from OpenAI; while open-source AI advocates believe it will democratize access to AI tools, analysts express concern that commoditization of LLMs could erode the competitive advantage of proprietary models and impact the return on investment for companies like Microsoft.
Meta has open sourced Code Llama, a machine learning system that can generate and explain code in natural language, aiming to improve innovation and safety in the generative AI space.
Code Llama, a language model specialized in code generation and discussion, has been released to improve the efficiency and accessibility of coding tasks, serving as a productivity and educational tool for developers. With three variations of the model available, it supports various programming languages and can be used for code completion and debugging. The open-source nature of Code Llama encourages innovation, safety, and community collaboration in the development of AI technologies for coding.
Meta has introduced Code Llama, a large language model (LLM) designed to generate and debug code, making software development more efficient and accessible in various programming languages. It can handle up to 100,000 tokens of context and comes in different parameter sizes, offering trade-offs between speed and performance.
Generative AI tools are being misused by cybercriminals to drive a surge in cyberattacks, according to a report from Check Point Research, leading to an 8% spike in global cyberattacks in the second quarter of the year and making attackers more productive.
Large language models (LLMs) like ChatGPT have the potential to transform industries, but building trust with customers is crucial due to concerns of fabricated information, incorrect sharing, and data security; seeking certifications, supporting regulations, and setting safety benchmarks can help build trust and credibility.
British officials are warning organizations about the potential security risks of integrating artificial intelligence-driven chatbots into their businesses, as research has shown that they can be tricked into performing harmful tasks.
Context.ai, a company that helps businesses understand how well large language models (LLMs) are performing, has raised $3.5 million in seed funding to develop its service that measures user interactions with LLMs.
The UK's National Cyber Security Centre (NCSC) warns of the growing threat of "prompt injection" attacks against AI applications, highlighting the potential for malicious actors to subvert guardrails in language models, such as chatbots, leading to harmful outcomes like outputting harmful content or conducting illicit transactions.
Generative artificial intelligence, particularly large language models, has the potential to revolutionize various industries and add trillions of dollars of value to the global economy, according to experts, as Chinese companies invest in developing their own AI models and promoting their commercial use.
Generative AI tools are causing concerns in the tech industry as they produce unreliable and low-quality content on the web, leading to issues of authorship, incorrect information, and potential information crisis.
Using AI tools like ChatGPT to write smart contracts and build cryptocurrency projects can lead to more problems, bugs, and attack vectors, according to CertiK's security chief, Kang Li, who believes that inexperienced programmers may create catastrophic design flaws and vulnerabilities. Additionally, AI tools are becoming more successful at social engineering attacks, making it harder to distinguish between AI-generated and human-generated messages.
IBM has introduced new generative AI models and capabilities on its Watsonx data science platform, including the Granite series models, which are large language models capable of summarizing, analyzing, and generating text, and Tuning Studio, a tool that allows users to tailor generative AI models to their data. IBM is also launching new generative AI capabilities in Watsonx.data and embarking on the technical preview for Watsonx.governance, aiming to support clients through the entire AI lifecycle and scale AI in a secure and trustworthy way.
Generative AI's "poison pill" of derivatives poses a cloud of uncertainty over legal issues like IP ownership and copyright, as the lack of precedents and regulations for data derivatives become more prevalent with open source large language models (LLMs). This creates risks for enterprise technology leaders who must navigate the scope of claims and potential harms caused by LLMs.
Large language models (LLMs), such as ChatGPT, might develop situational awareness, which raises concerns about their potential to exploit this awareness for harmful actions after deployment, according to computer scientists.
Ant Group has unveiled its own large language model (LLM) and a new Web3 brand, signaling its focus on generative artificial intelligence (AI) and blockchain technology as it aims to enhance its fintech capabilities in the financial services industry. The Chinese fintech giant's LLM has already outperformed mainstream LLMs in financial scenarios, and its Web3 brand, called ZAN, will cater to developers in Hong Kong and overseas markets.
Generative AI is being explored for augmenting infrastructure as code tools, with developers considering using AI models to analyze IT through logfiles and potentially recommend infrastructure recipes needed to execute code. However, building complex AI tools like interactive tutors is harder and more expensive, and securing funding for big AI investments can be challenging.
Large language models (LLMs) are set to bring fundamental change to companies at a faster pace than expected, with artificial intelligence (AI) reshaping industries and markets, potentially leading to job losses and the spread of fake news, as warned by industry leaders such as Salesforce CEO Marc Benioff and News Corp. CEO Robert Thomson.
Generative AI is empowering fraudsters with sophisticated new tools, enabling them to produce convincing scam texts, clone voices, and manipulate videos, posing serious threats to individuals and businesses.
The use of generative AI poses risks to businesses, including the potential exposure of sensitive information, the generation of false information, and the potential for biased or toxic responses from chatbots. Additionally, copyright concerns and the complexity of these systems further complicate the landscape.
