HN758: How Selector Built an AI Language Model for Networking (Sponsored)
Nov 15, 2024
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John Capobianco, an expert in network automation and AI at Selector, discusses the revolutionary impact of AI on networking operations. He dives into the customization of AI language models specifically for networks, enhancing job performance and simplifying management. The conversation highlights real-world applications, the integration of natural language queries, and the benefits of tailored models for data privacy. Capobianco also shares insights on the upcoming Packet Copilot tool, designed to aid engineers in analyzing network data effortlessly.
Selector.ai utilizes AI to enhance network operations through customized language models that provide actionable insights from network data.
The network language model by Selector.ai offers near real-time fine-tuning, allowing rapid adaptation to the evolving network conditions.
Selector.ai serves as a co-pilot for network engineers, augmenting existing tools by improving monitoring capabilities and reducing resolution times.
Deep dives
Introduction of AI in Network Operations
Artificial intelligence (AI) is becoming increasingly valuable in network operations, especially through the work of companies like Selector.ai. Selector.ai specializes in AIOps for networking and not only processes existing documentation but also taps into the data generated by networks to draw meaningful insights. The approach emphasizes a customized integration of large language models, specifically fine-tuning them to cater to individual network environments. This is seen as a significant step beyond traditional methods, promising enhanced operational efficiency and more accurate network management.
The Network Language Model Explained
At the core of Selector's offering is a network language model, which is a fine-tuned version of a large language model (LLM) specifically developed for network data. This model ingests telemetry data, SNMP, syslogs, and other relevant information, enabling it to produce contextually aware responses in natural language. By utilizing techniques like retrieval augmented fine-tuning, it can convert SQL queries into conversational language that users can easily understand. This allows users to simply ask their network-related questions and receive intelligent, actionable feedback.
Real-Time Data Processing and Fine-Tuning
The network language model offers near real-time fine-tuning, operating on defined training cycles between five to fifteen minutes to refresh its understanding of network conditions. This rapid adaptation means that responses to queries can be updated frequently without significant delays, allowing for timely insights into network status. The fine-tuning process leverages unique customer data, ensuring that each organization benefits from a secure and personalized model. This effectively transforms the approach to network management from reactive to proactive, anticipating issues before they escalate.
Augmentation of Existing Network Tools
Selector.ai is designed to augment rather than replace existing network management tools, effectively serving as a co-pilot for network engineers. By integrating machine learning and AI, it enhances traditional tools like SolarWinds and Splunk with improved monitoring capabilities and reduced false positives. Its ability to correlate root causes and streamline troubleshooting leads to significantly reduced resolution times for networking issues. This model not only increases efficiency but also democratizes network operations, making it accessible to professionals at all skill levels.
Practical Applications and Use Cases
Potential use cases for Selector.ai abound, offering scalable solutions across various industries, including manufacturing and healthcare. For example, users can quickly identify issues such as slow application performance by analyzing comprehensive data across the network and suggesting immediate fixes. Furthermore, the system provides advanced alerting capabilities that can notify teams in natural language, aiding in swift decision-making. Enhanced visualization tools also allow for effective monitoring and problem-solving, benefiting both seasoned network professionals and newcomers to the field.
On today’s episode, artificial intelligence with sponsor Selector.AI. If you’re curious and maybe still skeptical about the value AI brings to network operations, listen to this episode. Selector is on the forefront of AIOps for networking, building models that are customized and specifically targeted at networks. What Selector is doing is NOT simply the low-hanging... Read more »
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