Understanding AI models to future-proof your AppSec program
Become more knowledgeable when talking about AI
Artificial Intelligence (AI) used to be considered a tool that only exists in fantasy. Today, it is a real application that's seamlessly used in our day-to-day life. Because of the wide use of Generate AI tools like ChatGPT, people have limited their definition of AI to large language models (LLM), but perception is different from reality, AI is much more than LLMs.
This asset from Snyk defines the different ways businesses can use AI. It explains the difference between narrow AI, logical AI, statistical AI, and generative AI, and it offers insight into how these technologies can be applied at every stage of software development.
This quick read will help you become more knowledgeable when talking to colleagues about AI, as it will help you identify:
- How close AI is to historical descriptions
- Concrete use-case scenarios for AI
- How to map out AI categories.
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Provided by Snyk
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The NCSC is calling for a crackdown on shadow AINews Organizations are urged to identify shadow AI use and tighten up security procedures
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Microsoft has joined the growing list of companies cracking down on ‘tokenmaxxing’News The company is updating internal guidance to reduce rising costs
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3 ways to get your data AI-readySponsored Data placement, preparation, and orchestration make or break an AI project – and the Dell AI Data Platform reduces the strain on enterprise IT teams across both storage and the data foundation
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‘What we’re seeing right now is just rapid escalation in AI token spend’: Accenture tells staff to stop using AI for unnecessary tasks amid surging costsNews Accenture has told some staff to roll back the use of AI for basic tasks while the consultancy grapples with surging AI token costs.
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‘The claims in the suit are false’: Workday hits back amid lawsuit claiming AI recruitment discriminationNews Is AI hiring discriminatory? A California judge has given the go-ahead for a class action suit against Workday
