What Is The Best Strategy When Startup Plays Slot Machines ?

Startup should take Upper-confidence bound strategy. Upper-confidence bound strategy is known as the algorithm is based on the principle of optimism in the face of uncertainty.

What Is The Best Strategy When Startup Plays Slot Machines ?

Does early-stage startup try highly risky things to explore breakthrough, or does startup exploit current situation and knowledge to make the best out of it?

Early-stage startup is definitely designed to implement the former, but average people feel uncomfortable on unstable situation startup faced with repeatedly. We cannot ignore cost of exploration. It could pressure team heavily.

In my hypothesis, startup with qualified product tends to show more robustness than startup without it. Qualified product allow us to reduce exploration cost. Early-stage startup is exploration machine, so efficiency of exploration and enough number of trials is vital factor to accomplish target.

Qualified product solves problem on member’s emotional aspect. Anxiety or doubt by members is one of the most dangerous factors that halt the business. Performance of team is relying on how members sees situation it is included. If members of team consider it hopeless, it is the time of rethink.

Startup should take Upper-confidence bound strategy. Upper-confidence bound strategy is known as the algorithm is based on the principle of optimism in the face of uncertainty, which is to select your options as if the circumstance is as nifty as is naturally possible. It is about being optimistic for uncertainty and keeping choosing the most plausibly best options.

Actually we don’t know enough about the option, we can not precisely estimate the return the option will give us. we are bound to learn more and improve our future estimations by exploring exploration space.

Options with high uncertainty usually lead to a lot of new knowledge. We can expect reward from failures startup made. It is desirable to share new knowledge as soon as failed startup have it, but startups are competing each other, so we can’t enjoy fully sharing of the Information.

I think most of startups never finish comprehensive exploration process in the field they targeted, since team is easy to lose enough capability after a series of failure. So, I think very small team is favorable to early stage exploration, for the purpose of reducing possibility of chaotic situation and moving quick in random world.

Reference

Bandit Algorithms “The Upper Confidence Bound Algorithm”

Photo by Krissia Cruz on Unsplash

Read more

AI時代のエッジ戦略 - Fastly プロダクト責任者コンプトンが展望を語る

AI時代のエッジ戦略 - Fastly プロダクト責任者コンプトンが展望を語る

Fastlyは、LLMのAPI応答をキャッシュすることで、コスト削減と高速化を実現する「Fastly AI Accelerator」の提供を開始した。キップ・コンプトン最高プロダクト責任者(CPO)は、類似した質問への応答を再利用し、効率的な処理を可能にすると説明した。さらに、コンプトンは、エッジコンピューティングの利点を活かしたパーソナライズや、エッジにおけるGPUの経済性、セキュリティへの取り組みなど、FastlyのAI戦略について語った。

By 吉田拓史
宮崎市が実践するゼロトラスト:Google Cloud 採用で災害対応を強化し、市民サービス向上へ

宮崎市が実践するゼロトラスト:Google Cloud 採用で災害対応を強化し、市民サービス向上へ

Google Cloudは10月8日、「自治体におけるゼロトラスト セキュリティ 実現に向けて」と題した記者説明会を開催し、自治体向けにゼロトラストセキュリティ導入を支援するプログラムを発表した。宮崎市の事例では、Google WorkspaceやChrome Enterprise Premiumなどを導入し、災害時の情報共有の効率化などに成功したようだ。

By 吉田拓史