AlexMikhalev

Create test for terraphim_mcp_server

Exported on 20/06/2025 at 8:08:52 BST from Cursor (1.1.3)

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User

Using @rust-sdk.md or @https://github.com/modelcontextprotocol/rust-sdk/tree/main/examples/clients example create a test for terraphim_mcp_server

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AlexMikhalev

{
  "id": "Server",
  "global_shortcut": "Ctrl+X",
  "roles": {
    "Engineer": {
      "shortname": "Engineer",
      "name": "Engineer",
      "relevance_function": "terraphim-graph",
      "theme": "lumen",
      "kg": {

AlexMikhalev

fabric -y "https://www.youtube.com/watch?v=JTU8Ha4Jyfc" --stream --pattern write_essay What Language Models Can and Can't Do

In this fascinating interview, AI researcher François Chollet offers his insights on the capabilities and limitations of modern large language models (LLMs). He argues that while LLMs have achieved impressive performance on many benchmarks, this does not necessarily translate to true intelligence.

Chollet makes the key point that intelligence is fundamentally about the ability to handle novelty - to deal with situations you've never seen before and come up with suitable models on the fly. This is something current LLMs struggle with. If you ask them to solve problems that are significantly different from their training data, they will often fail.

The reason, Chollet explains, is that LLMs are essentially just very sophisticated "interpolative databases." They memorize an enormous number of functions and patterns from their training data, and when queried, they retrieve and combine t

AlexMikhalev

fabric -y "https://www.youtube.com/watch?v=JTU8Ha4Jyfc" --stream --pattern extract_wisdom SUMMARY: François Chollet discusses intelligence, the limitations of large language models, and his work on measuring intelligence with the Abstraction and Reasoning Corpus (ARC) in an interview with Tim.

IDEAS:

• Intelligence is the ability to handle novelty and come up with models on the fly.
• Large language models fail at solving problems significantly different from their training data.
• The Abstraction Reasoning Corpus (ARC) is designed to be resistant to memorization.
• Introspection is effective for understanding how the mind handles system 2 thinking.
• Scale is not all you need in AI; performance increase is orthogonal to intelligence.

AlexMikhalev

{
	"ignored_packages":
	[
		"LSP-rust-analyzer",
		"Rust",
		"Solarized Color Scheme",
		"SublimeLinter",
		"SublimeLinter-flake8",
		"Terminus",
		"Theme - Spacegray",

AlexMikhalev

Course design cards #scss

A Pen by Kristen on CodePen.

License.

AlexMikhalev

#!/bin/bash

bucket_name="my-unique-name"
aws s3api create-bucket --bucket "${bucket_name}" > /dev/null # 1
aws s3api put-public-access-block --bucket "${bucket_name}" --public-access-block-configuration "BlockPublicPolicy=false" # 2
aws s3api put-bucket-policy --bucket "${bucket_name}" --policy '{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "PublicReadGetObject",

AlexMikhalev

[
	{ "keys": ["alt+shift+p"], "command": "show_overlay", "args": {"overlay": "command_palette"} },
	{ "keys": ["ctrl+k","ctrl+a"], "command": "select_all" },
	{ "keys": ["ctrl+e"], "command": "move_to", "args": {"to": "eol", "extend": false} },
	{ "keys": ["ctrl+a"], "command": "move_to", "args": {"to": "bol", "extend": false} },
	{ "keys": ["shift+right"], "command": "lsp_symbol_definition",
	 "args": {"side_by_side": false, "force_group": true, "fallback": false, "group": -1},
        "context": [
            {"key": "lsp.session_with_capability", "operand": "definitionProvider"},
            {"key": "auto_complete_visible", "operand": false}

AlexMikhalev

# Editor Config
theme = "catppuccin_macchiato"

[editor]
scrolloff = 6
mouse = true
middle-click-paste = true
scroll-lines = 3
shell = [ "zsh","-c" ]
line-number = "absolute"

AlexMikhalev

import time

time_ns = time.monotonic_ns()