The Top 100 AI Consumer Apps ranked!

Hope you had an amazing week! There have been a lot of tools in the A.I. Space getting upgrades, like MidJourney and Luma Labs.

Big partnerships were made to train data and a few walk throughs to help you get started. Catch up in the latest AI News Update below!

HERE IS THE BREAKDOWN:

• Top 100 GEN AI Consumer APPS

• Quick Headlines and Tools to Try

• In Depth Walkthroughs to help you get started

• Salesforce introduced two AI Powered Sales Agents

• Amazon Q has saved 4,500 developer years of work

TOP 100 GEN AI CONSUMER APPS

Andreessen Horowitz released their 3rd edition of their top 100 Consumer Apps and it is fascinating to see what people are using. I personally know and use a lot of these, but I would reorder them in my opinion. What do you think?

QUICK HEADLINES AND TOOLS TO TRY

• D-ID Launched AI Video Translate and can translate voice and lip movements into other languages seamlessly

• Cursor launched where people can now create code at a high level just by speaking to their computer

• Adobe introduces Magic Fixup for easy photo editing

• High quality Text to 3D is here with Meshy-4

• Ideogram enters the mix with high end text generation in images

• Krea AI added Flux-1 to their platform for much better quality of image generation

• Boston Dynamics Robot can now do pushups!

TOOL WALK THROUGHS

SALES WILL NEVER BE THE SAME AGAIN

Salesforce has unveiled two groundbreaking AI-powered tools aimed at revolutionizing sales processes: Einstein SDR Agent and Einstein Sales Coach Agent. These innovative solutions are designed to address the perennial challenge of building and maintaining a robust sales pipeline while enhancing the skills of sales professionals.

Key Points:

1. Einstein SDR Agent autonomously engages with inbound prospects 24/7, qualifying leads and nurturing the sales pipeline.

2. Einstein Sales Coach Agent provides a virtual environment for salespeople to rehearse pitches and offers real-time suggestions during live calls with prospects.

3. The AI agents are positioned as team members to augment human capabilities rather than replace salespeople.

4. Salesforce's Data Cloud and RAG (Retrieval-Augmented Generation) technology power these AI solutions, leveraging various language models from OpenAI, Anthropic, and internal developments.

Why This Is Important:

These AI-driven sales tools represent a significant leap in sales technology, addressing critical challenges in pipeline management and sales enablement. By automating lead qualification and providing personalized coaching, Salesforce's AI agents have the potential to dramatically increase sales productivity, especially for smaller firms with limited resources. As the adoption of AI in sales processes grows, it could reshape the entire sales landscape, making it crucial for businesses to stay informed and consider implementing such technologies to remain competitive in an increasingly AI-driven market.

AMAZON SAVING YEARS OF DEVELOPERS WORK

Amazon's CEO Andy Jassy has announced that their AI software assistant, Amazon Q, has revolutionized the company's software development processes, saving an equivalent of 4,500 developer-years in labor. This remarkable achievement highlights the transformative potential of AI in streamlining software development and maintenance tasks.

Key Points:

1. Amazon Q has dramatically reduced the time required to update Java applications from 50 developer-days to just hours.

2. Within six months, over half of Amazon's production Java systems have been upgraded, a process traditionally considered tedious and often postponed.

3. 79% of the automatically generated code reviews have been deployed without further modifications, showcasing the AI's accuracy and efficiency.

4. The improved efficiency is projected to result in annual savings of approximately $260 million through enhanced security and reduced infrastructure costs.

Why This Is Important:

Amazon Q's success in automating and accelerating software maintenance tasks represents a significant breakthrough in enterprise software development. This development not only demonstrates the potential for AI to tackle traditionally time-consuming and monotonous tasks but also highlights substantial cost savings and improved security outcomes. As more companies explore AI-driven solutions for software development and maintenance, we may see a shift in how large-scale IT projects are managed and executed, potentially leading to faster innovation cycles and more robust software ecosystems across various industries.