Eric Hoel published a spot-on analysis of AI disruptiveness, including this gem:
The easier it is to train an AI to do something, the less economically valuable that thing is. After all, the huge supply of the thing is how the AI got so good in the first place.
TL&DR: AI can easily disrupt things that are easy to generate and thus have little value. Seeing investors trying to recoup the billions pouring into the latest fad will be fun.
Gerben Wierda published another AI-buster article describing what exactly “state-of-the-art” means in AI benchmarks.
Hint: you give an AI model 32 step-by-step examples before asking a question, and it still gets it wrong 10% of the time.
Gerben Wierda published another AI-buster article describing what exactly “state-of-the-art” means in AI benchmarks.
Hint: you give an AI model 32 step-by-step examples before asking a question, and it still gets it wrong 10% of the time.
SD-WAN and SASE are evolving to encompass more features and capabilities around security, application performance, network visibility, and more. On today's Heavy Networking, sponsored by Palo Alto Networks, we look at how AI is transforming SD-WAN and SASE to help build the branch of the future.
The post HN714: Building The Branch Of The Future With SASE Powered By AI (Sponsored) appeared first on Packet Pushers.
This is part two of a special edition of Day Two Cloud with conversations recorded at KubeCon 2023 in Chicago. These conversations cover the state of cloud-native security, getting a holistic view of your cloud-native environment, security challenges for Kubernetes, and the state of the software supply chain.
The post D2C225: Security KubeConversations Part 2 – Cloud-Native Security Challenges appeared first on Packet Pushers.
After a brief introduction of how the language models fit into the AI/ML landscape, Javier Antich explained the language model basics, including auto-regression, types of language models, the specifics of large language models, and potential use cases,
After a brief introduction of how the language models fit into the AI/ML landscape, Javier Antich explained the language model basics, including auto-regression, types of language models, the specifics of large language models, and potential use cases,
Performance tuning, in general, requires a holistic view of the application traffic profiles, features leveraged and the criteria for performance from the application perspective. In this blog, we will take a look at some of the factors to consider when optimizing NSX for performance.
In a typical data center, applications may have different requirements based on their traffic profile. Some applications such as backup services, log files and certain types of web traffic etc., may be able to leverage all the available bandwidth. These long traffic flows with large packets are called elephant flows. These applications with elephant flows, in general, are not sensitive to latency.
In contrast, in-memory databases, message queuing services such as Kafka, and certain Telco applications may be sensitive to latency. These traffic flows, which are short lived and use smaller packets are generally called mice flows. Applications with mice flows are not generally bandwidth hungry.
While in general, virtual datacenters may be running a mixed set of workloads which should run as is without much tuning, there may be instances where one may have to tune to optimize performance for specific applications. For example, applications Continue reading
Cloud engineer Leonard Pahlke talks about his experience over six terms on the Kubernetes release team, from joining to moving through various roles. He emphasizes the importance of community involvement, the welcoming nature of open source and cloud native fields, and the diverse opportunities for contribution.
The post KU043: How (& Why) To Contribute To The Kubernetes Release Team appeared first on Packet Pushers.
This episode looks at 2023 milestones for IPv6, including overall adoption levels, security advancements, and the state of IPv6-only in the enterprise.
The post IPB141: IPv6 End Of Year Wrap-Up appeared first on Packet Pushers.
In order for one device to talk to other devices on the Internet using the aptly named Internet Protocol (IP), it must first be assigned a unique numerical address. What this address looks like depends on the version of IP being used: IPv4 or IPv6.
IPv4 was first deployed in 1983. It’s the IP version that gave birth to the modern Internet and still remains dominant today. IPv6 can be traced back to as early as 1998, but only in the last decade did it start to gain significant traction — rising from less than 1% to somewhere between 30 and 40%, depending on who’s reporting and what and how they’re measuring.
With the growth in connected devices far exceeding the number of IPv4 addresses available, and its costs rising, the much larger address space provided by IPv6 should have made it the dominant protocol by now. However, as we’ll see, this is not the case.
Cloudflare has been a strong advocate of IPv6 for many years and, through Cloudflare Radar, we’ve been closely following IPv6 adoption across the Internet. At three years old, Radar is still a relatively recent platform. To go further back in time, we Continue reading
TL&DR: If you’re using netlab to build labs for your personal use, you can skip this one, but if you plan to use it to create training labs (like my BGP labs project), you might want to keep reading.
Like any complex enough tool, netlab eventually had to deal with inconsistent version-specific functionality and configuration syntax (OK, topology attributes). I stumbled upon this challenge when I wanted to make labs that use two types of configurable devices.
TL&DR: If you’re using netlab to build labs for your personal use, you can skip this one, but if you plan to use it to create training labs (like my BGP labs project), you might want to keep reading.
Like any complex enough tool, netlab eventually had to deal with inconsistent version-specific functionality and configuration syntax (OK, topology attributes). I stumbled upon this challenge when I wanted to make labs that use two types of configurable devices.