Adding more clarification

notebooks/03_get_embeddings.ipynb

@@ -8,6 +8,24 @@
     "# Pre-requisites"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "5f625807-0707-4e2f-a0e0-8fbcdf08c865",
+   "metadata": {},
+   "source": [
+    "## Why TEI\n",
+    "There are 2 **unsung** challenges with RAG at scale:\n",
+    "1. Getting the embeddings efficiently\n",
+    "1. Efficient ingestion into the vector DB\n",
+    "\n",
+    "The issue with `1.` is that there are techniques but they are not widely *applied*. TEI solves a number of aspects:\n",
+    "- Token Based Dynamic Batching\n",
+    "- Using latest optimizations (Flash Attention, Candle and cuBLASLt)\n",
+    "- Fast loading with safetensors\n",
+    "\n",
+    "The issue with `2.` is that it takes a bit of planning. We wont go much into that side of things here though."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "3102abce-ea42-4da6-8c98-c6dd4edf7f0b",
@@ -297,6 +315,7 @@
     }
    ],
    "source": [
+    "%%time\n",
     "# Create a list of async tasks\n",
     "tasks = [main(documents[i:i+MAX_WORKERS]) for i in range(0, len(documents), MAX_WORKERS)]\n",
     "\n",