Schlagwort: English language

5 Productivity Hacks to improve your Meeting Culture

Everyone has experienced days that are almost completely filled with meetings. Since business trips have become redundant due to the Covid-19 pandemic and you no longer need to plan in any travel time, it is very tempting to fill in the remaining gaps in your schedule with new tasks – and in the worst case, there is no time for lunch.

Is this the type of modern work we want to experience? Below we have put together some ideas and suggestions that can help to make your working day more pleasant.

1. 5-minute breaks after meetings

A 5-minute break after a meeting can be incredibly revitalizing – especially when meetings are often back-to-back. Outlook gives you the option to automatically schedule meetings 5 minutes shorter:

Once you have shortened your meetings by 5 minutes, you need to make sure that everyone sticks to it.

2. Blocker for lunch breaks, daycare, etc.

To make sure nobody schedules a meeting during your lunch break, a lunch blocker can help you here. Just create an appointment series:

If all the colleagues in your team create a lunch blocker for the same time, it’s (almost) like having lunch together.

If you also have children who need to be taken to daycare, kindergarten, or school, an appointment series can serve the same purpose here. As it is usually possible to make calls while in the car, you can also leave a note with your phone number in the appointment series so that your colleagues know how to reach you when you’re on the road.

3. Chat und Call Etiquette

When pinging colleagues on Teams, don’t simply write “Hello”, as each message distracts them from their current task. While you are typing the remaining message, your colleague is very likely to wait until you have sent it. Even though it might seem impolite or even rushed at first, it is easier for your colleagues if you get right to the point. It is therefore a good idea to type the whole message and send it in one go.

The same goes for calls. Instead of pinging a colleague before calling them and typing “Hello” or “Hello, are you free for a quick call?” it’s better to give them some information beforehand, such as the topic and the estimated duration of the call. For example, you could write “Hello, do you have 3 minutes to discuss topic XYZ with me?” That allows your counterpart to estimate whether they can take the time for this particular call.

For more information on chat and call etiquette, check out this link: aka.ms/NoHello

4. Reduce meetings

To reduce the number of meetings you need to attend, it is helpful to ask yourself the following questions before sending out meeting invites:

  • Can the question be clarified by chat or email?
  • Is this matter urgent or can it wait until the next regular team meeting?
  • Do we really need to involve everyone or are fewer participants enough?

Each meeting should be critically questioned and the most important meetings prioritized. Before attending a meeting, it helps to ask yourself the question: Do I have an active contribution to make to the meeting, or do I only need to read the meeting minutes?

5. Using AI-based technologies

Do not hesitate to actively leverage AI-based technologies. MyAnalytics gives you the option to automatically block focus times. With just one click, not only dedicated times can be blocked for you, but these blockers also automatically change your status on Teams to “Don’t Disturb”. Thus you can simulate, for example, your travel times. More information about the features of MyAnalytics can be found by following this link.

Outlook also gives you various options that can help you save time and focus on the essentials. You can use email rules to automatically move mail to different Outlook folders. For example, you can determine that all cc messages are placed in a separate folder. That allows you to dedicate time to reading these messages as required. The goal is that at the end of the day your inbox is empty (zero-inbox policy) so that you can start afresh the next day. You can also deactivate Outlook push notifications so that you are not distracted by pop up notifications during important activities.

What are your ideas for a more productive workday? We’d like to read your suggestions in the comments below.

Written by Sophia Cullen and Alexander Loth. This post is also published on LinkedIn. Also, this post has influenced some of the thoughts in our new book, Decisively Digital (www.decisivelydigital.org).

Decisively Digital book
Decisively Digital book

Recap of the 17th Data & AI Meetup: Data & AI in Healthcare

Analyzing Medical Images: Detecting Pneumonia with Custom Vision
Analyzing Medical Images: Detecting Pneumonia with Custom Vision AI

Recently we had the 17th edition of our Data & AI Meetup. This meetup focused on Data & AI in Healthcare. Let’s have a quick recap!

Agenda:

16:00 – Willkommen & Intro
16:05 – BI as a Service für eine bessere Healthcare Supply Chain
Christopher Glogger, Sana Einkauf & Logistik
16:35 – AI Trends und Use cases
Andreas Kopp, Microsoft
17:20 – Visuelle Datenanalyse rund um CoViD-19
Markus Raatz, Ceteris AG
17:55 – Wrap up

Session recording:

Further information:

The next Data & AI Meetup?

The next Data & AI Meetup will be announced on the Data & AI LinkedIn group and on the Data & AI Meetup page. Feel free to join!

If you’ve dreamed of sharing your Data & AI story with many like-minded Data & AI enthusiasts, please submit your session proposal.

GPT-3: A Leap in Language Generation But Not True AGI– Insights from Decisively Digital

Explore the intricate relationship between AGI and GPT models like OpenAI's GPT-3, as revealed in the much-awaited book "Decisively Digital."
Explore the intricate relationship between AGI and GPT models like OpenAI’s GPT-3, as revealed in the much-awaited book „Decisively Digital.“

Artificial Intelligence (AI) has been making significant strides in recent years, particularly in the realm of generative AI. Among these advancements, OpenAI’s GPT-3 (Generative Pre-trained Transformer 3) has emerged as a groundbreaker. While its language generation capabilities are astonishing, the question remains: Are we any closer to achieving Artificial General Intelligence (AGI)? In this article, we’ll explore the complex world of GPT-3, its potential, and its limitations, as discussed in my forthcoming book Decisively Digital.

The Evolution of Generative AI and GPT-3’s Arrival

Generative AI has seen considerable growth in recent years. OpenAI first introduced GPT-3 in a research paper published in May and subsequently initiated a private beta phase. Selected developers have been granted access to further explore GPT-3’s capabilities. OpenAI has plans to turn this tool into a commercial product later this year, offering businesses a paid subscription to the AI via the cloud.

The Capabilities of GPT-3

The evolution of large language models like GPT-3 is worth examining in the context of Natural Language Processing (NLP) applications. From answering questions to generating Python code, GPT-3’s use cases are expanding by the day. Generative AI has been escalating at an unprecedented rate. OpenAI’s recent launch of GPT-3 has created a buzz in both the tech community and beyond.

The software has moved into its private beta phase, with OpenAI planning to offer a cloud-based commercial subscription later this year. This move marks a significant stride toward integrating GPT models into business applications, bringing us one step closer to the AGI GPT reality.

The Marvel of GPT-3: A Milestone in AGI Evolution?

GPT-3 is a machine-learning model with an impressive 175 billion parameters, making it capable of generating astonishingly human-like text. It’s been applied to numerous tasks, from generating short stories to even coding HTML. These capabilities have been turning heads and inciting discussions around AGI GPT models. But is it all it’s cracked up to be?

GPT-3’s predecessor, GPT-2, laid the foundation for the current model. While the underlying technology hasn’t changed much, what distinguishes GPT-3 is its sheer size—175 billion parameters compared to other language models like T5, which has 11 billion parameters. This scale is a result of extensive training on data largely sourced from the internet, enabling GPT-3 to reach or even surpass current State-Of-The-Art benchmarks in various tasks.

The Limitations and Weaknesses

Despite its staggering capabilities, the GPT-3 model is not without its flaws. Despite its human-like text generation capabilities, GPT-3 is still prone to generating hateful, sexist, and racist language. It’s a powerful tool but lacks the genuine smarts and depth that come with human cognition. In essence, while the output may look human-like, it often reads more like a well-crafted collage of internet snippets than original thought.

Most people tend to share positive examples that fit their bias towards the machine’s language „understanding.“ However, the negative implications, such as the generation of offensive or harmful content, need to be considered seriously. For example, GPT-3 has been found to generate racist stories when prompted with specific inputs, which raises concerns about the technology potentially doing more harm than good.

Not Quite AGI

Many have been quick to label GPT-3 as a stepping stone towards AGI. However, this might be an overestimation. GPT-3 can make glaring errors that reveal a lack of common sense, a key element in genuine intelligence. As OpenAI co-founder Sam Altman notes:

„AI is going to change the world, but GPT-3 is just a very early glimpse. We have a lot still to figure out.“

Sam Altman, CEO, OpenAI

Decisively Digital: The AGI GPT Discourse

My upcoming book Decisively Digital devotes an entire chapter to the role of GPT-3 in business and its potential to serve as a stepping stone toward AGI. From automating customer service to generating insightful reports, GPT-3 offers a wealth of opportunities for enterprises. However, the book also delves into the ethical considerations and potential pitfalls of adopting this powerful technology.

Concluding Thoughts: AGI GPT—A Long Road Ahead

While GPT-3 serves as an intriguing glimpse into the future of AGI, it is just that—a glimpse. We have a long road ahead in the quest for AGI GPT models that can mimic true human intelligence. As we navigate this fascinating journey, a balanced perspective is crucial.

To stay updated on these critical topics and much more, connect with me on Twitter and LinkedIn, and be on the lookout for the release of Decisively Digital.

Recap of the 16th Data & AI Meetup: Azure Bootcamp

Azure Synapse Analytics Screenshot
Azure Synapse Analytics demo shown during the meetup

Yesterday we had the 16th edition of our Data & AI Meetup. This meetup was a hands-on Azure Bootcamp. Let’s have a quick recap!

Agenda:

  1. Welcome & Intro
  2. Azure SQL DB
  3. Azure Data Factory
  4. Azure Synapse Analytics
  5. Visual Analytics with Power BI on Azure

Session recording:

Further information:

The next Data & AI Meetup?

The next Data & AI Meetup will be announced on the Data & AI LinkedIn group and on the Data & AI Meetup page. Feel free to join!

If you’ve dreamed of sharing your Data & AI story with many like-minded Data & AI enthusiasts, please submit your session proposal.