Zapier Central Bots VS OpenAI GPTs - is it a clear winner?
Summary
TLDRスクリプトのエッセンスを提供する魅力的な要約で、ユーザーの興味を引き、関心を喚起する。
Takeaways
- 🚀 ZapierはOpenAIのGPTと競争している可能性があると話題に
- 🌟 Zapierのユーザーは、Zaps、テーブル、チャットボット、キャンバスなど多くの変更に気づいているでしょう
- 📊 テーブルはデータベースインターフェース、フォーム、アプリのようなインターフェースを提供
- 🤖 チャットボットはZapierで簡単に構築し、他のアプリと統合して展開できる
- 🎨 カンバスを使用して、Zapierが提供する要素をリンクしてZapsやAutomations、より大きなフローに使用できる
- 🔧 Zapier Centralの登場で、これらの要素が集約される可能性が示されている
- 🔍 新しいZapier Centralのインターフェースでは、ボットの作成が可能
- 📈 GPTと同様に、Zapier Centralではボットの振る舞いやデータソースを設定できる
- 📨 テストとして、肥胖度確率のGPTを使用してZapier Centralの機能を検証
- 📚 データソースとしてGoogleシートを使用し、特定の年齢や性別で肥満確率を計算するロジックを作成
- 📩 トリガーとアクションを設定し、Gmailアカウントを通じてAIがメールを送信する
- 🔥 ZapierのAIが独自にロジックを構築し、エラーなく実行できることが示唆されている
- 🌐 Zapierは6,000のアプリを統合しているため、この新機能は非常に大きなポテンシャルを持っている
- 💡 Zapier Centralがさらに発展すれば、GPTやGPT市場にとって大きな問題になる可能性がある
Q & A
Zapierの最新の変更は何ですか?
-Zapierの最新の変更は、Zaps、テーブル、チャットボット、そしてキャンバスの導入です。Zapsは自動化、テーブルはデータベースインターフェース、チャットボットは簡単なアプリ構築、キャンバスはこれらの要素をリンクして自動化や大きなフローに使用できるようにすることです。
Zapier Centralはどのようなものですか?
-Zapier Centralは、Zapierのユーザーがボットを構築するためのプラットフォームです。これにより、ユーザーはGPTのような機能をZapierのインターフェース内で直接使用できます。
Zapierのボットはどのように動作しますか?
-Zapierのボットは、ユーザーが提供したトリガーとデータソースに基づいて動作します。ユーザーが設定したトリガーに応答し、指定されたアクションを実行します。
Zapierのボットで使用されるデータソースは何ですか?
-この例では、Googleシートがデータソースとして使用されており、人の年齢、BMI、身長、体重、活動レベルなどの情報が含まれています。
Zapierのボットはどのようにして動作を定義しますか?
-Zapierのボットは、ユーザーが設定したトリガーとアクションに基づいて動作を定義します。たとえば、特定のフレーズやキーワードがトリガーになり、それに対してボットは指定されたアクションを実行します。
Zapierのボットが実行した結果はどのように表示されますか?
-Zapierのボットが実行した結果は、コードブロックとして表示され、自動的に生成されたロジックが含まれています。この例では、データベースから情報を取得し、指定されたメールアドレスに結果を送信するというアクションが含まれています。
Zapierのボットはどのようにしてエラーを回避しましたか?
-Zapierのボットは、ユーザーが提供した指示とデータソースに基づいて自動的にロジックを構築し、実行することで、以前のGPTとZapierアクションの統合で発生したエラーを回避しました。
ZapierのボットとGPTの違いは何ですか?
-Zapierのボットは、GPTの機能をZapierのインターフェース内で直接使用できるようにし、自動化とアプリ構築のためのツールとして機能します。また、Zapierは6,000以上のアプリとの統合が可能で、さらに多くの機能性を提供する可能性があります。
Zapierのボットはどのようにして名前を付けられますか?
-Zapierのボットは、ユーザーが作成した際に名前を付けることができます。この例では、名前が付けられていないため、「Untitled Bot」となっています。
Zapier Centralにアクセスできるのはどのようなユーザーですか?
-Zapier Centralにアクセスできるユーザーは、Zapierのスーパーユーザーや一部のテストユーザーなど、特別に招待されているユーザーとなります。
Zapierのボットを使用する際に期待される利点は何ですか?
-Zapierのボットを使用することで、GPTのような機能をZapierのプラットフォーム内で直接利用できること、自動化とアプリ構築のためのツールとしての利便性、さらには6,000以上のアプリとの統合による拡張性が期待できます。
Outlines
😮 Zapierの進化とGPT機能の統合
このパラグラフでは、Zapierのプラットフォームがどのように進化してきたか、そして最近のGPT機能の統合に焦点を当てています。以前は単純な自動化ツールであったZapierが、データベース、ユーザーインタフェース、チャットボット、そしてキャンバス機能を含むより複雑なサービスに拡大したことが説明されています。特に、新しく導入された「Zapier Central」は、これらの要素が統合され、ユーザーがGPTのような機能を使ってより高度な自動化と対話を設計できるようになっていることが強調されています。ユーザーはZapierを通じてデータソースを管理し、AIを用いて具体的なタスクを実行する自動化を作成できます。
🤖 ZapierのAI機能の実用例と潜在能力
このパラグラフでは、ZapierのAI機能の実用例とその潜在能力について詳しく説明されています。特に、著者は肥満率を計算するためのボットをテストし、ZapierのAIがデータベースから情報を引き出し、ロジックを自動的に生成してメールで結果を送信する過程を詳述しています。このAI機能により、従来のコード記述やバックエンド開発を大幅に削減し、直感的かつ効率的な自動化プロセスを実現しています。ZapierのAIは、6,000以上のアプリケーションとの統合機能を持ち、複雑なタスクを簡単に実行できるため、GPT技術を超える可能性があることが示唆されています。
Mindmap
Keywords
💡Zapier
💡GPT
💡Zaps
💡Tables
💡Chatbots
💡Canvas
💡Zapier Central
💡AI
💡Google Sheet
💡Probability
💡Integration
Highlights
Zapier has introduced significant changes for its users, impacting the interface and functionality.
The traditional concept of 'Zaps' has evolved to include new features like tables, interfaces, chatbots, and canvas.
Zapier's tables serve as a database interface, similar to an app interface, enhancing user experience.
Chatbots on Zapier simplify the process of building, integrating, and deploying bots with other applications.
Canvas allows users to link various elements provided by Zapier into complex automation flows.
Zapier Central is a new feature that seems to integrate all the new functionalities.
The interface for creating bots in Zapier Central is user-friendly and intuitive.
Zapier's bot development includes defining bot behavior and data sources.
A practical example given is an obesity probability GPT that can be tested within Zapier.
Zapier allows integration with external data sources, such as a Google Sheet, for bot operations.
Bots can be triggered by specific phrases or keywords, and then perform actions like sending an email.
AI within Zapier can generate values for fields and execute actions based on user instructions.
The AI built into Zapier can understand and execute complex logic without backend development.
Zapier's AI can execute tasks more smoothly and with fewer errors than traditional GPT methods.
Zapier's potential to integrate with 6,000 apps could revolutionize automation and AI applications.
Zapier's advancements may pose a significant challenge to the GPT market and OpenAI's dominance.
Users might prefer Zapier for complex projects due to its ease of use and integration capabilities.
Zapier's AI capabilities might outperform traditional GPTs in practical applications.
Transcripts
Hello everyone, this is maybe not an episode, I just
thought to drop off this quick video, is Zapier beating
OpenAI in the GPT game now?
So for some time if you are a Zapier user,
you've probably noticed lots of changes, and you can see
such changes when you look at the Zapier screen.
So in the past we used to have Zaps, it's
all about the Zaps and the automations you actually can
build on Zapier.
Then later they added tables, interfaces, chatbots now and canvas.
Now Zaps is the automation, tables is as I said
the database interface is that forms or even app like
kind of interface that you might have, chatbots they made
it very easy to take it, build it in Zapier,
integrate it with other apps and then deploy it.
Then canvas where you can basically link these elements that
they are providing either in beta or now firm kind
of elements into their interface for you to use and
build upon, you can link them together in Zaps and
automations and at bigger flows.
What I stumbled upon now that they have something called
the Zapier Central where I feel all of that might
come together.
Now it looks like this as you see on the
screen now.
So you're creating a bot essentially, so now if you
look at it this is the interface that you get
when you go to the central.zapier.com.
I'm not sure if everyone gets it, maybe I'm just
one of the lucky ones that got it as a
user, I can call myself a super user of Zapier.
The way I would describe it, it's a GPT.
I've covered in two videos that I will put the
link for in the description GPT builds and one of
them I really focus on trying to create actions through
Zapier actions which never worked really well.
Now they're delivering it to you through the Zapier interface.
I don't know where this is going but definitely it
is interesting.
So two things you can provide or work with when
you're considering to go through the Zapier Central and their
bots.
Number one, how the bot behaves, so you can see
on the screen here the behavior and then the data
sources.
So let's test it quickly.
One of the videos I did recently is the obesity
probability GPT.
I will test it quickly here, I will not go
into detail just to see how it works, maybe in
the future we can cover this in more detail.
So let me add a source, it's very limited as
of now.
So let me go for a Google Sheet and this
is the account.
Let me try to find the obesity probability.
It's the same one I built the API upon in
Xano.
So I will add that as a data source.
It has information about people, their age, their BMI, height,
weight, activity level, all these things.
And then let me get a behavior, let me add
a creative behavior.
Let me add a trigger.
So basically the trigger is a message to the bot,
specific phrase or keyword.
So for the specific phrase, I put probability because the
GPT I created is basically people asking to get their
probability of being obese at a specific age and gender.
So that's the trigger through talking to the bot.
So I added the trigger and then the action, let's
make it send an email, which we tested in the
GPT with Zapier actions and had lots of errors.
And here the action is basically a Gmail, send mail,
the connection, the account, basically my account, my email, and
then two have AI generate a value for this field
as you would do in a GPT kind of training.
So, or action development or action setting in the configuration
of the GPT.
And then even for the CC have the AI generate
the value for this field.
So everything is set up by the AI.
I'm just here confirming that it has to use my
Gmail account to perform this action.
So let's add that action.
So for the instructions, I have basically told it whenever
someone asked for the probability of being underweight, overweight, just
basically take their age, take their weight and create those
probability of those different categories of weight.
So under, over, normal and obese and send it to
their email after they provide it.
Very generic.
This is something we did not do in the GPT
because we wanted to always respond in a consistent manner.
So we created the logic in the Xano API in
the back end, and then we connected the API to
the GPT.
Here I'm going to stress test the brains of the
AI that Zapier is dropping now to us all.
So let's check how the behavior works and see what
we get.
Wow.
Okay.
This is, I think it's smarter than the GPT.
I already can see something beyond the GPT.
So it analyzed the database.
It was really sharp in doing so.
And then it's asking me for more information than I
put in the instructions because I wanted to make it
simple.
It took that already from the database that to calculate
probabilities, it needs the weight, the height, and then my
email address.
It missed having said that the gender to just to
showcase what they just dropped Zapier.
Let me just test it later on.
We can do a more in depth kind of analysis
for this.
So here I'm giving my height, my weight, and then
my email as per instructed by the AI.
This is not trained yet.
So I didn't really train it as you do in
a GPT.
This is impressive.
So it took some time in running and what I
can see here, and by the way, it's called Untitled
Bot because I didn't give it a name.
You can name it, but basically if you look here,
it created a code block.
You can see a code.
So basically it did the logic by itself.
So what I've done in the backend in Zano, it
did here.
The AI did it for me and then it executed
on it.
So it retrieved the data from the database and it
sent the email.
Now I got a notification on my mobile and I
can see the email here.
And basically it gave me only the probability of being
obese based on the height and weight, which is 19.1%.
Impressive stuff.
I think this has lots of potential.
I think this might beat the GPTs unless they do
something extraordinary, not only because it is really smart, but
for two specific reasons, at least I can articulate and
think about now.
Number one, it coded the logic for me from my
instructions, from the database, from everything that I've provided.
It made some sense of what I might be looking
for.
And this is what you expect from AI.
And then it built it for me and actually executed
smoothly without any errors, any issues.
Now, if I go back and maybe fix it and
feed it more details around my expectation, probably it will
operate even better.
I somehow skipped the backend development kind of thing and
I have a working GPT or a bot and I
am sure at some point, either I can deploy this
through interfaces or on a website through their bots function
on Zapier website.
The other thing is the huge potential when you're talking
about Zapier, they have 6,000 apps working and integrating within
this platform.
Think about what you might be able to do smoothly
going forward with this.
I think this is big news.
Maybe it's not somewhere open AI is willing or even
thinking about competing, but if it is, definitely Zapier is
at least as of what I see now will be
a big problem for the GPTs and GPT market.
I know they are partnering together and probably they will
work together towards better outcome of these kinds of projects.
If I am today using a GPT and I want
to develop something maybe solid or more complex, maybe I'll
go through the route of working in Zapier rather than
GPT.
If Zapier really puts their weight behind this and they
develop it even further.
Did you have access if you're a Zapier user?
Did you gain access to the Zapier central?
Do you want specific use cases that I shall experiment
with using specific apps?
Write me a comment in the comment section below and
hey if you like it hit the like button and
subscribe thank you very much and goodbye
5.0 / 5 (0 votes)