Network Break 420: Cisco, HPE Buy Security Startups; Can We Finally Hold Vendors Responsible For Software Defects?

Take a Network Break! We begin with some FU on what constitutes on-prem and off-prem, and then dive into news. Cisco and T-Mobile are partnering on 5G gateways, Cisco Webex is getting installed as a feature(?) in Mercedes E-Class cars, and Cisco is buying multi-cloud security startup Valtix. Valtix offers firewalling, IPS, a cloud Web app firewall, and more for the big 4 US clouds. The White House releases its National Cybersecurity Strategy which includes a proposal to make vendors liable for significant software defects, SNIA releases a new standard for memory-to-memory data movement, and IBM acquires DNS provider NS1. Meta announces a Large Language Model (LLM) that can run on a single GPU, HPE buys Axis security to add cloud-delivered security services to its portfolio, and HPE announced it lost half a billion dollars in Q1 of its fiscal 2023. APNIC beats back an activist contingent in recent elections, and LastPass discloses that attackers got access to a key employee’s laptop. Get links to all these stories below. Show Links: Investor Relations – Cisco @ Mobile World Congress: Showcasing Simple and Secure Wireless Experiences to Help Businesses Connect More People and Things – Cisco Cisco Launches Meraki 5G Gateways with T-Mobile to Deliver Simple and Scalable Business Internet – Cisco Simplify and Scale Anywhere Connectivity – Cisco Systems Investor Relations – Mercedes-Benz AG Partners with Cisco to Drive Hybrid Work Innovation in Automotive – Cisco Accelerating Our Security Cloud Vision: Cisco Announces Intent to Acquire Valtix  – Cisco Blogs National Cybersecurity Strategy – White House SNIA’s New Smart Data Accelerator Interface Specification – SNIA IBM Plans to Acquire NS1 to Help Enterprises Drive Network Agility in their Hybrid Cloud Environments – IBM NetBoxLabs Blog – NetBox Labs Meta unveils a new large language model that can run on a single GPU [Updated] – Ars Technica LLaMA: Open and Efficient Foundation Language Models – Meta