My response is going to be about Gemini generally and less about NotebookLM.
Google's last frontier model release was Gemini 3.1 Pro, which was in February of this year[1]. At the time, it was ahead of the (at the time) flagship models of Opus 4.6 and GPT 5.2/5.3. From my recollection of the time, it was the best model in the world.
Anthropic released Opus 4.5 Nov '25, 4.6 in Feb '26, 4.7 in April, 4.8 in (late) May. Then Fable in June. 4.7 beat 3.1 Pro on multiple metrics. Fable eats it for breakfast. However, I want to note the 3 month gap between those first two Opus versions.
OpenAI released 5.2 Dec '25, 5.3 Codex Feb '26, 5.3 Instant Mar, 5.4 Mar, 5.5 (late) May, 5.6 July. 5.4 beats 3.1 Pro on agentic benchmarks[2], seems to be similar/losing on non-agentic. 5.5 seems stronger than 3.1 Pro[3].
Gemini 3.5 Pro is alleged to be launching within the week. Why do I type this all out? Because I think Google is getting a bad rap. They are delayed on a frontier release by a month or two and are being regarded as if they cannot release frontier models. I think their last release demonstrates strength and we need to see a weak release before we call them "behind" (in any reasonable sense). These companies swap back and forth constantly. I recall a multi-month span where 2.5 Pro was just the best thing out there by a large margin (in my opinion).
In my experience, Gemini 3.x wasn’t just getting a bad rap, it was significantly worse in practice. It could analyze codebases and report back from a one-shot prompt as good as Claude or Codex but any slightly complex task that carried on for more than a few minutes led to hanging, seemingly infinite loops, and bizarre and nonsensical hallucinations, to the point of being unusable for serious work. The Claude and Codex counterpart models at the time rarely had such issues for the same type and duration of complex work, if at all. To be fair, later Claude especially started having hanging issues as many people noticed but that’s been better recently.
The author explain this in more detail in the article; I also was initially confused. The key details come from their broken down pandoc command. Specifically, these two flags:
--pdf-engine=typst
-V template=article.typ
Despite the input content being a .md file, we see that the .md contents populate the .typ file. Pandoc then understands how to convert the populated .typ file into a .pdf. The author also notes in their hyperlinked .typ document where the body content is placed:
// THIS IS THE ACTUAL BODY:
What is not clear to me is the actual mechanism that tells pandoc where to place the body contents in the template. I presume it's some "magic" from the pandoc docs. The pandoc templates documentation[1] does reveal to us that `-V` is setting a variable called `template`. I don't have pandoc locally, but from another post[2] from the same author and a chatgpt query, it seems that the `body` symbol in the template is the chosen substitution symbol.
Pandoc templates use $...$ or ${...} for variable substitution, yes. body is one of the special default variables: the rest are documented in the manual. If you scroll to the bottom of the template linked from the article, you'll notice a $body$, along with a number of $if(...)$ $endif$ conditionals.
(This actually interferes with Typst's math mode. But you can manually construct math blocks, so no real problem. Pandoc variables are only valid within templates anyway.)
I looked at Luma, but the website shows that for the part of Western Europe I'm in, it only supports Amsterdam or Brussels. Not even Cologne. Or am I using their website wrong?
I can't smell much at all. one time when i was 17 my friend told me i was kinda smelly (i had just exercised). I've been stressed about it since. the human brain can latch on to the oddest things
there is something "wrong" with the ux that is hard to pin down. these things generate even text summaries more rapidly than i can read them. i need a better method for dumping info into my brain + dynamic control (if necessary)
When I take time to read all of the output, I often find that it's mostly noise. I don't like noise so I usually don't bother.
But a person can use subagents, if they want, to filter that down. This burns tokens in a big hurry, but I think subagents can be arbitrary local commands (eg, a local LLM).
Or, you know: Just slow down. :) It doesn't always have to be a race, does it?
It would be nice if there was a whitelist option for non-sensitive content. I stopped using cdn links due to the overhead of the extra domain lookups but I did think that my self hosted content would be cached across domains.
It would be nice if there was a whitelist option for non-sensitive content.
There's no such thing as non-sensitive content from a CDN though. Scripts are obviously sensitive, styles can be used to exfiltrate data through background-url directives, and anything like images has no benefit being cached across sites.
Fonts might be one exception, but I bet those are exploitable somehow.
Google's last frontier model release was Gemini 3.1 Pro, which was in February of this year[1]. At the time, it was ahead of the (at the time) flagship models of Opus 4.6 and GPT 5.2/5.3. From my recollection of the time, it was the best model in the world.
Anthropic released Opus 4.5 Nov '25, 4.6 in Feb '26, 4.7 in April, 4.8 in (late) May. Then Fable in June. 4.7 beat 3.1 Pro on multiple metrics. Fable eats it for breakfast. However, I want to note the 3 month gap between those first two Opus versions.
OpenAI released 5.2 Dec '25, 5.3 Codex Feb '26, 5.3 Instant Mar, 5.4 Mar, 5.5 (late) May, 5.6 July. 5.4 beats 3.1 Pro on agentic benchmarks[2], seems to be similar/losing on non-agentic. 5.5 seems stronger than 3.1 Pro[3].
Gemini 3.5 Pro is alleged to be launching within the week. Why do I type this all out? Because I think Google is getting a bad rap. They are delayed on a frontier release by a month or two and are being regarded as if they cannot release frontier models. I think their last release demonstrates strength and we need to see a weak release before we call them "behind" (in any reasonable sense). These companies swap back and forth constantly. I recall a multi-month span where 2.5 Pro was just the best thing out there by a large margin (in my opinion).
[1]: https://blog.google/innovation-and-ai/models-and-research/ge...
[2]: https://www.anthropic.com/news/claude-opus-4-7
[3]: https://www.anthropic.com/news/claude-opus-4-8