Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]

Netflix created a scoring system from 0 to 100 that assigns a priority to a request, with 0 being the highest priority and 100 being the lowest priority.

The score was based on 4 dimensions

Functionality - What functionality gets impacted if this request gets throttled? Is it important to the user experience? For example, if logging-related requests ... See more

Customer empathy makes a comeback. Companies will move beyond the “best gen AI model” rat race by radically transforming everyday consumer and enterprise workflows with a rich and deep pipeline of category-specific capabilities for the long-tail of professional needs. I like how my friend Aaron Levie, founder of Box, recently described these layers... See more

Here are example ways to increase the success rate of these custom agents:

Provide a more focused, use-case specific system prompt to kick things off. Since you know what kinds of goals the agent supports, you can improve the odds of coming up with the right set of tasks initially. In fact, there’s nothing wrong with actually defining the set of tas... See more

When the CPython process starts up, it performs runtime initialization. The runtime contains critical data required for the operation of the rest of the virtual machine.

Next, the Python code gets parsed and compiled into bytecode instructions, this is called tier-1 bytecode. This compiled bytecode is interpreted by the tier-1 bytecode interpreter.

T... See more

Denormalization

Another way Reddit minimizes joins is by using denormalization.

They took all the metadata fields required for displaying an image post and put them together into a single JSONB field. Instead of fetching different fields and combining them, they can just fetch that single JSONB field.

This made it much more efficient to fetch all the ... See more

Increasing perversion of certain business models that are liable to be gamed or constrained by AI: We’re shifting from a world where data analysis required long cycles (analysts need lots of time to run queries, analyze, and then present findings in a way that people understand) to a new world of real-time optimization and insights (AI will mine th... See more

In a given construction project, there are often many stakeholders involved, especially in large projects:

Owners: They initiate construction projects, working with architects and engineers to design the project. They also hire a general contractor to operationally build the project.

General Contractors: They work for owners and are responsible for l... See more

core components of Deep RL that enabled success like AlphaGo: self-play and look-ahead planning.

Self-play is the idea that an agent can improve its gameplay by playing against slightly different versions of itself because it’ll progressively encounter more challenging situations. In the space of LLMs, it is almost certain that the largest portion o... See more

The need for better AI or LLM-specific infrastructure, along with the host of problems that come with non-deterministic of LLMs, means that there’s more software work ahead of us, not less. Abstraction layers like LLMs create more possibilities and thus, more work.

Is this a good thing or a bad thing? I’m not sure.

A great example of this is frontend... See more

𝗺𝗲𝘁𝗵𝗼𝗱𝘀 𝗼𝗳 𝗳𝗶𝗻𝗲-𝘁𝘂𝗻𝗶𝗻𝗴 𝗮𝗻 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲 𝗟𝗟𝗠 𝗲𝘅𝗶𝘀t ↓

- 𝘊𝘰𝘯𝘵𝘪𝘯𝘶𝘦𝘥 𝘱𝘳𝘦-𝘵𝘳𝘢𝘪𝘯𝘪𝘯𝘨: utilize domain-specific data to apply the same pre-training process (next token prediction) on the pre-trained (base) model

- 𝘐𝘯𝘴𝘵𝘳𝘶𝘤𝘵𝘪𝘰𝘯 𝘧𝘪𝘯𝘦-𝘵𝘶𝘯𝘪𝘯𝘨: the pre-trained (base) model is fine-tuned on ... See more