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Oliver Molander
Oliver Molander

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Sep 6

Gartner’s AI Hype Cycle is Way Passed its Due Date — And Are We Entering a Classical ML Winter?

When looking at Gartner’s 2023 Hype Cycle for Artificial Intelligence one can only come to one conclusion: the hype cycle itself has reached its ‘Peak of inflated expectations’ and is way past its due date. — Those who know me also know that I’m NOT a big fan of Gartner Hype Cycles. Or Gartner Magic Quadrants. Or Forrester Waves for that matter… The reality is that the ‘technologies’ Gartner tracks miss a lot of the foundational, transformative ones. What Gartner tracks, maps to the vendor technology…

Large Language Models

11 min read

Gartner’s AI Hype Cycle — Way Passed its Due Date… And are We Entering a Classical ML Winter?
Gartner’s AI Hype Cycle — Way Passed its Due Date… And are We Entering a Classical ML Winter?
Large Language Models

11 min read


Jun 22

The $113M Mistral AI Seed Round — Why So Much Hate? And Why Europe Should be an AI Powerhouse

I’ve seen a lot of frustration towards Mistral AI and their $113M seed round on social media lately. Here are some of my reflections about it. But before we start I have to, of course, point out that we wouldn’t be here without Transformer models (first described in the Google Brain paper in 2017), which changed the game for language models. — Let’s deep-dive right away into it. I’ve decided to write this article mainly in a bullet-point format to make it snappier. I also recommend looking through the 7-page Mistral AI investment memo published by Sifted below:

Mistral

14 min read

The $113M Mistral AI seed round — why so much hate?
The $113M Mistral AI seed round — why so much hate?
Mistral

14 min read


Published in

Better Programming

·Updated Apr 3

Thoughts on Twitter ‘open sourcing’ its recommendation algorithm — and learnings for startups and VCs

Since the end of November and the launch of ChatGPT, the discussion around AI/ML has been entirely dominated by generative AI, Large Language Models, and Foundation Models. This is for a good reason some may say, as the masses have realized the power of these models, especially when they’re fine-tuned with reinforcement learning from human feedback. But it’s equally important to understand that AI/ML is much more than just LLMs & Foundation Models. I briefly wrote about this in my post about the hype around LLMs and Foundation Models earlier in 2023. This was one of the reasons why it felt like a breath of fresh air when Twitter decided to open source its recommendation algorithm — something that Elon had been teasing about for a while.

Startup

11 min read

Thoughts on Twitter ‘open sourcing’ its recommendation algorithm — and learnings for startups and…
Thoughts on Twitter ‘open sourcing’ its recommendation algorithm — and learnings for startups and…
Startup

11 min read


Mar 3

How did this B2B SaaS startup founded in 2020 raise a $300M round at a $10B valuation in early 2023?

Wiz — a multi-cloud security startup founded in 2020 — just raised 300M$ at a $10B valuation. In this market climate. How is this possible? 🤯 — Well, Wiz is unique in many ways, but most importantly the startup is a masterclass of top-percentile business execution, founder-market fit and playing on strong secular tailwinds with the right GTM. Wiz is the fastest SaaS company to reach $100M in ARR and $200M in ARR respectively and has changed…

Startup

4 min read

How did this B2B SaaS startup founded in 2020 raise a $300M round at a $10B valuation in early 2023?
How did this B2B SaaS startup founded in 2020 raise a $300M round at a $10B valuation in early 2023?
Startup

4 min read


Feb 23

Some personal musings around the YC W23 Generative AI Landscape

There are 36 AI/ML-related startups in this YC Winter Batch out of the 201 startups accepted in total. — This represents ca 18% of the current cohort being some kind of Generative AI startups. Is 18% a lot or not? Let’s compare this with the Y Combinator Winter & Summer Batch from ’21 when we were at peak Crypto & Web3 hype: The ’21 YC Winter Batch had in…

Startup

3 min read

Some personal musings around the YC W23 Generative AI Landscape
Some personal musings around the YC W23 Generative AI Landscape
Startup

3 min read


Feb 22

The 2023 edition of the Machine Learning, AI and Data Landscape — a quick analysis

The latest MAD (Machine Learning, AI and Data) Landscape is out again! A huge kudos for the tremendous work Matt Turck and the team FirstMark Capital have done putting the analysis together 🙌 — In this year’s landscape, there are 1,426 companies, compared to 139 companies in the first landscape from 2012. This represents an +1,000% increase in a decade!

Machine Learning

4 min read

The 2023 edition of the Machine Learning, AI and Data Landscape — a quick analysis
The 2023 edition of the Machine Learning, AI and Data Landscape — a quick analysis
Machine Learning

4 min read


Published in

Better Programming

·Feb 9

The greatest startup turnaround in developer tooling history — and learnings for founders

In the US alone 340 unicorns were minted in 2021 according to data from PitchBook. This compared to 100 new US unicorns minted in 2020, 78 unicorns in 2019, 62 unicorns in 2018, 35 unicorns in 2017 and 21 unicorns in 2016. In 2021 it felt like new +$1B companies were minted every hour. We’ve not only experience overall inflation, but unicorn inflation like never seen before — not only in the US but globally.

Docker

19 min read

The greatest startup turnaround in developer tooling history — and learnings for founders
The greatest startup turnaround in developer tooling history — and learnings for founders
Docker

19 min read


Published in

Better Programming

·Updated Mar 2

ChatGPT, LLMs, and Foundation models — a closer look into the hype and implications for startups

We’ve all seen the craze around generative AI via e.g. ChatGPT, DALL-E, and Stable Diffusion. GPT-4 is rumored to be even more mind-blowing. There are plenty of open questions about these models, their accuracy, and even their legality from an IP perspective. And from the startup and investor perspective, there are serious concerns about whether one can build a defensible business on top of any of these types of foundation model platforms. But hype cycles come and go. Many are not aware of this, but we’ve had several AI hype cycles followed by several AI winters. Did you know that the first chatbot launched was Eliza in 1964? It was an early natural language processing computer program created from 1964 to 1966 at the MIT Artificial Intelligence Laboratory by Joseph Weizenbaum.

Gpt 3

37 min read

ChatGPT, LLMs and Foundation models — a closer look into the hype and implications for startups
ChatGPT, LLMs and Foundation models — a closer look into the hype and implications for startups
Gpt 3

37 min read


Published in

Better Programming

·Updated Dec 29, 2022

DuckDB — What’s the Hype About?

This was a blog post that I already planned to write during the spring when I saw that the hype around DuckDB started taking new heights. Since then the discussion around DuckDB has only intensified in the developer and data engineering community. I currently see two trends within the data community with high engagement levels: DuckDB and Rust taking over data engineering. But what’s the hype around DuckDB really about? Let’s scratch the surface a little bit.

Data Engineering

10 min read

DuckDB — What’s the Hype About?
DuckDB — What’s the Hype About?
Data Engineering

10 min read


Published in

Better Programming

·Nov 10, 2022

Is It Time To Rebrand (or Rethink) the Modern Data Stack?

In a few weeks, it will be exactly ten years since AWS Redshift was made public for the first time through a limited preview. Redshift is considered the O.G. cloud data warehouse, followed by BigQuery and Snowflake. …

Data Engineering

6 min read

Is It Time To Rebrand (or Rethink) the Modern Data Stack?
Is It Time To Rebrand (or Rethink) the Modern Data Stack?
Data Engineering

6 min read

Oliver Molander

Oliver Molander

866 Followers

Preaching about the realities and possibilities of data and machine learning. Founder & investor.

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