#Productivity Metrics

[bmpmp3]

i was watching a music video for a japanese song and it had built in youtube english captions so i went to turn those on but then i saw that there was like an option for "English" and then a second option for "English (Canada)" and i realized in a few seconds it was just a workaround to having two sets of english captions, one with colour changes in the lettering and one without for accessibility (the canada one was the non-fancy lettering) but for a moment i was living in a world where they were making dedicated canadian english translations for things..... measuring temperature in celsius and height in feet...... paying with loonies and toonies... going to the WASHROOM

[intobarbarians]

my boss wants us to keep track of our time on TWO different programs and has been harping on about keeping the doors to our offices open. for bonding.

[walterdecourceys]

my new procrastination thing is making a little interactive flowchart that tells you which chess production you should watch first. which is proving to be harder than it sounds

[ryanthedemiboy]

Fuck monopolies, fuck artificial scarcity, fuck kroger.

[maareyas]

i am once again wishing i would either be transformed into a mindless animal that only follows instincts and my own desires and isn't bound by the complex and arbitrary rules of living in a human civilization, or into a robot devoid of desire and individuality that only lives for a purpose

instead im trapped as some dumbass ape that is stuck in between these two extremes and have gotten the worst of both

[buriedwithoutceremony]

recommend me 2 albums and tell me why you like them?

!!!!! I'm going to do 5 instead because I'm too indecisive.

5. Hissing Fauna, Are You The Destroyer? by Of Montreal. I love the first seven tracks of this album to bits and if it ended there it might be my favorite album. Of Montreal's sound is always unique and this album in particular is such a journey and full of pathos, I think it's truly a masterclass in album-building, with how it manages the rise of energy into the at-first-placid whirlpool of The Past is a Grotesque Animal. But it lands at #5 because I inherently don't trust break up albums by men and the latter half sinks more and more into that, and def has some kinda misogynistic lines, esp. on track 11.

4. Lost on You, by LP. My fave album by lesbian power-icon LP, it's deliciously weary. I'll say her genre (more blues-ey in this one, but with one country/gospel vibes) is not my thing generally... but with her it works for me, and this album really nails it. The eponymous track within the album is one of my top 3 tracks of all time. Now that's a break up song.

3. The Black Parade, by MCR. Look I. How do I even begin? I feel like @butchviking could cover this better than I could ever hope to. I Though I am slightly afraid she might have me butchered in bed for ranking it only 3rd. Anyway great capstone to my emo boy days, thank you for your service Mr. Grard Ouias.

2. Melody of Certain Damaged Lemons, by the Blonde Redhead. Okay Blonde Redhead is probably my favorite group, and I had a hard time picking an album and I didn't want overrepresent. But honestly I love their whole range and if you have the time I recommend checking them out, they have such a unique sound and have gone through so many interesting phases and influences. Lemons specifically is, to me, a great merger of their more accessible later stuff and their more raw and weird earlier stuff, art punk but maybe a bit more art than punk. 23 and Misery is a Butterfly are also rock solid albums.

1. Box of Secrets, by Blood Red Shoes. Thrashing around to this whole album for 15 minutes is the cheat code to fixing my brain. Heeheehoo!

[howldean]

weeping i love my therapist

[thepotatofrog]

anybody know where i can pay to watch a movie where most of the money is actually going to the creators instead of the platform? i’m so fucking done with netflix and everything else but there’s some things where i just really really want to support the creators

[aadmelioraa]

due to the sheer size of my blocklist i don’t see many mundane bad rings of power takes in the tag these days, but the ones i do see are so supremely terrible they’re almost impressive

[softgrungeprophet]

You are allowed to do hobbies for fun! just fyi!

[handleerz]

[definedge99]

Optimizing Performance: A Comprehensive Guide to Key Performance Indicators (KPIs)

A Performance Indicator is a measurable value used to evaluate the success of an organization, individual, or process in achieving goals. It helps assess efficiency, productivity, and progress, guiding decision-making for improvements and strategic planning.

[jcmarchi]

📽 [Webinar] Beat GPT-4 with a Small Model and 10 Rows of Data*

New Post has been published on https://thedigitalinsider.com/webinar-beat-gpt-4-with-a-small-model-and-10-rows-of-data/

📽 [Webinar] Beat GPT-4 with a Small Model and 10 Rows of Data*

Small language models (SLMs) are increasingly rivaling the performance of large foundation models like GPT-4. However, the need for high-quality datasets for fine-tuning these models presents a persistent challenge. 

On August 8th, Predibase is going to showcase an approach for fine-tuning an SLM that outperforms GPT-4 with synthetic data generated from only 10 real-world examples.

The Data Dilemma

While fine-tuning SLMs with high-quality datasets can consistently produce task-specific models that outperform large foundation models, many teams face a significant barrier: assembling sufficient training data. This challenge has often been a bottleneck in AI development, limiting the ability of teams to develop production-ready models quickly and cost-effectively.

Synthetic Data Through Distillation

Our upcoming webinar introduces an innovative solution to this persistent challenge. By leveraging the capabilities of large language models such as GPT-4 and Llama-3.1-405b, we’ve developed techniques to generate high-quality synthetic data for fine-tuning task-specific SLMs. This approach enables teams to achieve GPT-4 level results with as few as 10 real-world examples, dramatically reducing the data collection burden and accelerating the path to production.

In this comprehensive session, we’ll delve into the following key areas:

The Data Insufficiency Challenge: We’ll explore the persistent issue of insufficient training data in AI development, discussing the limitations it imposes on teams working with SLMs.

Synthetic Data Generation Techniques: Our ML team will demonstrate methods for generating high-quality synthetic data based on as few as 10 data rows using Llama-3.1-405B and GPT-4. 

Achieving GPT-4 Level Performance: We’ll show how SLMs fine-tuned with synthetic data can match or exceed the performance of GPT-4 across various tasks. Attendees will gain insights into the fine-tuning process, hyperparameter optimization, and performance evaluation metrics.

Streamlining the Development Process: We’ll discuss strategies for significantly reducing data collection efforts and accelerating the journey from concept to production. This includes techniques for identifying key seed examples, automating the synthetic data generation pipeline, and optimizing the fine-tuning workflow.

Join us on August 8th

Whether you’re an AI practitioner, startup founder, or enterprise decision-maker, this session will equip you with knowledge to effectively use synthetic data and SLMs. Join us to explore how synthetic data and fine-tuned SLMs can unblock your AI initiatives. Register today.

*This post was written by Will Van Eaton from Predibase. We thank Predibase for their insights and ongoing support of TheSequence.

[gunkyengines]

•••

Hey what's the deal with lumping people who don't give a fuck about the pro/anti discourse in with one side or another in their DNIs now. This is absolutely not something where not picking a side means picking a side. (More thoughts in the tags.)

[maxlearnmicrolearningplatform]

Mastering Microlearning: Navigating Success with a Production Mindset

In the realm of modern education and professional development, microlearning stands out as a dynamic approach to delivering targeted knowledge efficiently. However, ensuring the success of a microlearning initiative requires more than just good intentions; it demands a production mindset focused on proactive planning, meticulous execution, and continuous improvement. This article delves into actionable strategies and insights aimed at steering microlearning endeavors away from failure and towards lasting impact, all under the guiding light of a production mindset.

Embrace a Proactive Planning Approach:

Success in microlearning begins long before content creation. Start by conducting a thorough needs analysis to identify learning objectives, audience demographics, and delivery preferences. Engage stakeholders early on to gain buy-in and align expectations with organizational goals. By laying a solid foundation through proactive planning, you set the stage for a successful microlearning journey.

Foster Collaboration and Cross-Functional Teams:

Microlearning initiatives thrive in environments where collaboration flourishes. Form cross-functional teams comprising instructional designers, subject matter experts, multimedia specialists, and technology experts. Encourage open communication channels and leverage diverse perspectives to brainstorm innovative solutions and address challenges effectively. Collaboration fosters creativity and ensures that all aspects of microlearning production are meticulously crafted.

Cultivate an Iterative Development Process:

Adopt an iterative approach to microlearning development, wherein content is continually refined based on feedback and performance metrics. Break down the production process into manageable stages, allowing for frequent reviews and adjustments. Embrace agility and flexibility to respond promptly to changing needs and emerging trends. By treating microlearning development as an ongoing journey of improvement, you can iterate towards excellence with each iteration.

Prioritize User-Centric Design Principles:

At the heart of every successful microlearning initiative lies a deep understanding of the end-user. Prioritize user-centric design principles to create engaging and intuitive learning experiences. Consider factors such as accessibility, mobile-friendliness, and personalized learning pathways to cater to diverse learner needs. Conduct usability testing and gather feedback from learners throughout the production process to refine the user experience iteratively.

Leverage Technology and Automation Tools:

Harness the power of technology and automation tools to streamline microlearning production processes. Explore authoring tools, learning management systems (LMS), and content delivery platforms that facilitate content creation, distribution, and tracking. Automate repetitive tasks such as content formatting, assessment scoring, and progress tracking to free up time for creative endeavors. Technology serves as an enabler, empowering production teams to focus their efforts on value-adding activities.

Implement Robust Quality Assurance Protocols:

Quality assurance is paramount in ensuring the effectiveness and reliability of microlearning content. Establish robust quality assurance protocols to identify and rectify errors before deployment. Conduct thorough reviews for accuracy, relevance, and adherence to learning objectives. Test content across multiple devices and platforms to ensure seamless accessibility and compatibility. By upholding stringent quality standards, you instill confidence in learners and stakeholders alike.

Monitor Performance Metrics and Key Performance Indicators (KPIs):

Success in microlearning is measurable, provided you track the right performance metrics and key performance indicators (KPIs). Monitor learner engagement, completion rates, assessment scores, and knowledge retention metrics to gauge the effectiveness of your microlearning initiatives. Analyze data insights to identify trends, patterns, and areas for improvement. By leveraging data-driven insights, you can make informed decisions and optimize future microlearning content accordingly.

Foster a Culture of Continuous Learning and Improvement:

Embrace a culture of continuous learning and improvement within your organization, where experimentation and innovation are encouraged. Encourage production teams to share best practices, lessons learned, and success stories. Provide opportunities for professional development and upskilling to keep pace with evolving industry trends. Celebrate achievements and milestones along the microlearning journey, recognizing the collective efforts of all stakeholders involved.

By adopting a production mindset grounded in proactive planning, collaboration, iteration, user-centric design, technology integration, quality assurance, performance monitoring, and continuous improvement, organizations can avoid failure and unlock the full potential of microlearning as a transformative learning tool. With a steadfast commitment to excellence and innovation, the path to mastering microlearning becomes a rewarding endeavor marked by sustained success and learner empowerment.

[hranalytics]

Guide on How to Increase Your Employee's Productivity

Boosting employee productivity is pivotal for the success of any organization. It involves optimizing work processes, enhancing work environments and ensuring employees are engaged and motivated. With the right strategies, businesses can significantly enhance their overall performance and achieve their objectives more efficiently. This guide outlines practical steps to increase your employees' productivity by leveraging analytics and fostering a supportive work culture.

Optimize Work Processes with Analytics

The first step in enhancing productivity is to optimize work processes. This can be achieved by analyzing employee productivity data, which provides insights into how employees spend their time, which tasks consume the most resources and where bottlenecks occur. By understanding these patterns, managers can streamline workflows, eliminate unnecessary tasks and introduce automation where beneficial. This not only saves time but also allows employees to focus on high-impact activities that contribute more significantly to the organization's goals.

Foster a Supportive and Engaging Work Environment

Creating a supportive work environment is essential for enhancing productivity. This involves recognizing and addressing employee needs, providing growth opportunities and encouraging a positive work-life balance. Encouraging open communication and offering feedback can also help employees feel valued and engaged. Utilizing employee productivity analytics can help identify areas where employees may need more support or resources, enabling managers to make informed decisions to enhance the work environment and, consequently, productivity.

In conclusion, increasing your employees' productivity requires a strategic approach that combines the optimization of work processes with the creation of a supportive work environment. By effectively leveraging employee productivity analytics, organizations can gain valuable insights into how to improve workflows and employee engagement. Implementing these strategies can lead to a more productive, motivated and satisfied workforce, driving the organization toward its goals with greater efficiency and success.

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