Azure Machine Learning vs. Google Gemini vs. Microsoft 365 Copilot

For [a] data scientist require[d] to build a machine learning model, so he/she didn't worry about infrastructure to maintain it.

All kind of feature[s] such as train, build, deploy and monitor the machine learning model available in a single suite.

If someone has [their] own environment for ML studio, so there [it would] not [be] useful for them.

Gemini is well suited to help in customer service, to create summaries of emails sent by customers, generating possible responses to them, rephrasing communications, help create and then correct SQL queries, interpreting responses, it's not so good if you need to help with a sensitive topic due to it taking personally identifying information

Incentivized

I highly recommend its usage in Teams meetings to prepare a session transcript, meeting minutes,
next steps and recognize speech by person. Also within the meeting recording, there is separation between the people talking at the time. The Copilot image creation is very accurate and useful to
customize my PowerPoint presentations and other documents

Incentivized

• User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
• Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
• Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
• Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
• Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.

Incentivized

• Deep research for getting first business research draft from Gemini, post which i use series of prompts to improve it and use my understanding to refine it further
• Canvas to produce structured business topic research and newsletter. Direct edits to the sections and making client ready reports
• Learning mode to get help on step by step automation of AI workflows

Incentivized

• Good analysis of the ticket system at the service desk, so that this can be anticipated properly
• For the management of IT environments, quick examples of scripting for desired solutions
• For consultants and managers, they co-pilot a technical report into language understandable to a non-technical client, including a visual summary.

Incentivized

• It would be great to have text tips that could ease new users to the platform, especially if an error shows up
• Scenario-based documentation
• Pre-processing of modules that had been previously run. Sometimes they need to be re-run for no apparent reason

Incentivized

• Currently the document database caps out at 10, requiring us to condense some of our policies
• It's large context window is a blessing and a curse. Sometimes it stops generating half way through a very ambitious request as it delivers page after page of content
• There is no way to share Gems currently, so we have to publish guides to our employees on how to best configure them

Incentivized

• The quality of image generation in Microsoft Copilot could be improved. Compared to other AI platforms, Copilot's images often fall short in quality and frequently contain typos.
• When generating agents and chatbots, Microsoft Copilot currently doesn't appear to support file download functionality.
• The email reply function is useful, but the responses can sometimes be overly elaborate. It would be helpful to have more options for adjusting the tone.

Incentivized

Absolutely!!! I have a high regard for the product and will use it for years to come.

Incentivized

Easy and fastest way to develop, test, deploy and monitor the machine learning model.

- Easy to load the data set

-Drag and drop the process of the Machine learning life cycle.

Google Gemini Web UI provided an intuitive user experience with a collapsible side menu and a recent chat feature. It has a nice, clean design and easy-to-use "Ask Gemini" chat control with an integrated Tool menu that provides quick access to Deep Research and Create images options. One can also search for chats quickly and efficiently.

Incentivized

it is nearly perfect and it’s usability one of the main factors and contributing to the score is how versatile this tool is. it is vastly usable in a multitude of circumstances, and has a few limitations, but overall this product works well for what it is intended. It is very helpful for some otherwise time consuming tasks.

Support is nonexistent. It's very frustrating to try and find someone to actually talk to. The robot chatbots are just not well trained.

Incentivized

Not sure

It is easier to learn, it has a very cost effective license for use, it has native build and created for Azure cloud services, and that makes it perfect when compared against the alternatives. As a Microsoft tool, it has been built to contain many visual features and improved usability even for non-specialist users.

Incentivized

Hootsuite's OwlyGPT is great for social listening data, but Gemini is far ahead in terms of caption writing and other writing needs. Even for content creation ideas, I'd rather take the social listening insights then feed that to Gemini. ChatGPT I truly have never been a fan of. Gemini's interface has always intrigued me more and I find it to have great functionality. Lastly, I included Perplexity - just to note another tool I've used. Perplexity is great for deep research, but outside of this I would always go with Gemini.

Incentivized

I think It lost the race for now. I don't think Microsoft will keep investing on it since we have better tools outside their environment. In my opinion, Microsoft Copilot is not even in the benchmark tools and in the race for AGI. I think Microsoft is way behind and Microsoft Copilot suffered the lack of investment like the one made by its competitors.

Incentivized

• Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster;
• Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat.
• Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details

Incentivized

• Free way to gain another team member
• Helps me be more efficient and overcome blocks in my workflow
• Speeds up my ability to update our website's calendar by easily double if not more
• Allows me to dabble in areas that I have no expertise in such as coding

Incentivized

• It is too early to tell at the moment but I can see it as a positive moving forward
• The amount of time saved in creating content will be a huge asset for faculty
• The same holds true for students as they to will be able to safe a lot of time

Incentivized