Today's Newsletter Highlights:

• How to use the new ChatGPT app integrations, including DoorDash, Spotify, Uber, and others

• Amazon Announces Inference Chips Deal With Cerebras

• Meta Platforms Plans Major Layoffs as AI Costs Rise

• Best AI Tools

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How to use the new ChatGPT app integrations, including DoorDash, Spotify, Uber, and others

A new update allows ChatGPT to connect with popular apps like Spotify, Uber, and DoorDash. You can now use natural language to do tasks in ChatGPT. This means you don’t have to open each app by hand.

Here’s how it works and how to use it 👇

1️⃣ Connect an app to ChatGPT

Open ChatGPT.

Go to Settings → Apps / Connectors.

Select the app you want (Spotify, Uber, DoorDash, etc.).

Sign in and allow permissions.

Once connected, ChatGPT can interact with that service for you.

⚠️ Important: Connecting an account shares some app data, like your Spotify listening history. This helps the AI personalise your experience.

What you can do with these integrations

🎵 Spotify

You can ask ChatGPT:

“Create a workout playlist.”

“Make a playlist with only Coldplay songs.”

“Recommend music based on my taste.”

Your playlist will appear in your Spotify account.

🍔 DoorDash

You can say things like:

“Order a burger and fries near me.”

“Find the best pizza under $20.”

ChatGPT can search for restaurants and start your order through DoorDash.

🚗 Uber

You can request rides such as:

“Book an Uber to the airport at 7 PM.”

“Estimate the ride price to downtown.”

ChatGPT will handle the booking through Uber.

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Amazon Announces Inference Chips Deal With Cerebras

Amazon’s AI Chip Deal with Cerebras — What Happened

Amazon's cloud unit, AWS, has teamed up with AI chip startup Cerebras Systems for a few years. This collaboration aims to integrate Cerebras’ ultra-fast AI chips into AWS data centres.

The Goal: Make AI models respond much faster to user queries and applications.

Why This Deal Matters :

1️⃣ Focus on AI Inference The partnership centres on AI inference. A trained AI model creates answers for users. This happens in chatbots or coding assistants.

Training = teaching the model

Inference = using the model to respond

Most real-world AI activity occurs during inference, driving companies to enhance speed.

2️⃣ How the System Will Work The two companies will divide AI workloads across different chips:

AWS Trainium chips → process the prompt (prefill stage)

Cerebras CS-3 chips → generate the output (decode stage)

Both systems will connect in AWS data centres to quicken AI responses.

3️⃣ Faster AI Responses Cerebras says its chips offer quick inference. They often outpace traditional GPU setups.

This means:

faster chatbot replies

quicker coding assistance

speedier AI searches

4️⃣ A Direct Challenge to Nvidia Nvidia currently dominates the AI chip market. This deal shows that Amazon wants to rely less on Nvidia GPUs. Instead, it plans to build its own AI infrastructure. More competitors in the market lead to:

cheaper AI computing

faster innovation

Read More

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Meta Platforms Plans Major Layoffs as AI Costs Rise

Meta Platforms may cut around 20% of its workforce in upcoming layoffs. The company is making this decision. It is also investing a lot in artificial intelligence technology and infrastructure.

Meta currently employs around 79,000 people globally. A 20% cut would mean roughly 15,000 to 16,000 jobs could be lost if the plan proceeds. Discussions are still happening, so the final numbers and timing aren’t confirmed yet.

Reasons for Possible Job Cuts

1️⃣ Massive Spending on AI

CEO Mark Zuckerberg is pushing Meta towards AI. The company is investing heavily in:

• AI data centres

• Advanced AI models

• New AI research teams

Meta plans to spend hundreds of billions on AI infrastructure by 2028. This will increase cost pressures.

2️⃣ AI Can Replace Some Work

Executives believe AI tools can boost employee productivity. This could allow smaller teams to manage projects that once needed larger groups. In short, AI might lessen the need for certain roles within the company.

3️⃣ Restructuring After AI Setbacks

Reports say that Meta's new AI models have run into technical issues and delays. This has raised the pressure to cut costs and restructure, but also to keep investing heavily in AI.

Not Meta’s First Layoffs

Meta has already made significant job cuts in recent years:

• 11,000 employees laid off in 2022

• 10,000 more in 2023 during its “Year of Efficiency”

If new cuts occur, they could become the largest layoffs in Meta’s history.

Read More

Meta Platforms Plans Major Layoffs as AI Costs Rise

Meta Platforms may cut around 20% of its workforce in upcoming layoffs. The company is making this decision. It is also investing a lot in artificial intelligence technology and infrastructure.

Meta currently employs around 79,000 people globally. A 20% cut would mean roughly 15,000 to 16,000 jobs could be lost if the plan proceeds. Discussions are still happening, so the final numbers and timing aren’t confirmed yet.

Reasons for Possible Job Cuts

1️⃣ Massive Spending on AI

CEO Mark Zuckerberg is pushing Meta towards AI. The company is investing heavily in:

• AI data centres

• Advanced AI models

• New AI research teams

Meta plans to spend hundreds of billions on AI infrastructure by 2028. This will increase cost pressures.

2️⃣ AI Can Replace Some Work

Executives believe AI tools can boost employee productivity. This could allow smaller teams to manage projects that once needed larger groups. In short, AI might lessen the need for certain roles within the company.

3️⃣ Restructuring After AI Setbacks

Reports say that Meta's new AI models have run into technical issues and delays. This has raised the pressure to cut costs and restructure, but also to keep investing heavily in AI.

Not Meta’s First Layoffs

Meta has already made significant job cuts in recent years:

• 11,000 employees laid off in 2022

• 10,000 more in 2023 during its “Year of Efficiency”

If new cuts occur, they could become the largest layoffs in Meta’s history.

Read More

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