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7555 views · 4 years ago
Midwest PHP and Nomad PHP Join Forces!


Interested in sponsoring? Check out the prospectus



A little history

Several years ago I had the distinct privilege of founding Midwest PHP with Jonathan Sundquist. The goal was simple, to bring an affordable PHP conference to Minnesota and the midwest region.

Midwest PHP was created for one simple reason - there weren't a lot of alternatives, especially affordable ones. At the time, your choices were ZendCon in Silicon Valley, php[tek] in Chicago, or Northeast PHP in Boston. While Northeast PHP formed the blueprint of a community conference - it still required a flight and a costly hotel in Boston. I wanted something where local attendees, college students, and those just beginning in their PHP careers could go to learn, network, and become part of the PHP community.

Shortly after Midwest PHP was formed (originally we were using the name PHPFreeze - until Sundquist told me what a horrible idea it was), Adam Culp launched Sunshine PHP which has become one of the top community focused PHP conferences (but still requires that flight and hotel in Miami). Sundquist and I knew that any reasonable developer would still prefer to attend a conference in a blizzard than enjoy the beautiful Floridian weather (ok, that might not be it, but we still understood the need that existed).

After moving to California for my new job, Jonathan Sundquist continued to run Midwest PHP as more community conferences appeared. With his efforts, and the torch being passed to Mike Willbanks, Midwest PHP celebrated it's seventh consecutive year, becoming the longest continuously running PHP conference (if you go by formed date, if you go by actual conference date Sunshine PHP beats us out by a month).


A renewed focus


Developers at Midwest PHP

Because of the incredible work Jonathan and Mike have done, Midwest PHP has stood the test of time - and the peaks and valleys that come with any conference. With the shifts in the PHP community and the sad loss of several community conferences - we realized the need for Midwest PHP is more now than ever, and to meet that need we needed to reimagine the way the conference operated.

We also realized that the best way to make Midwest PHP accessible was to combine forces, creating a seamless partnership between Nomad PHP and Midwest PHP. Through this partnership we're not only able to stream the event to make it more accessible ($19.95/mo), but also expand the conference.

This year, taking place onApril 2-4, 2020 - Midwest PHP will bring together over 800 developers both in-person and virtually! Making this year truly unique, however, and staying with our purpose of helping new developers be part of the PHP community is abrand new, FREE, beginner track. I'm excited to say we will be giving away 200 tickets to those wishing to attend our Beginner or Learn PHP track!!!

We will also work to keep prices as low as possible as we offer our standard PHP tracks (Everyday PHP and PHP Performance & Security) starting at $250/ person, anda brand new enterprise track geared at developers facing challenges at unprecedented scale starting at $450/ person.

Last but not least, it is our goal with the help of our sponsors to include the workshop day as part of your ticket price - allowing you to get one day of in-depth training, and two more full days of sessions. On top of this, we're also excited to make the Nomad PHP and Nomad JS video libraries available for Standard and Enterprise attendees, providing over 220 additional virtual sessions on demand!


For sponsors

Sponsoring a conference is hard. We understand the challenge of gauging ROI, planning travel, and coordinating outreach. With the combined forces of Midwest PHP and Nomad PHP, we're able to offer sponsors unique plans that maximize their investment - while ensuring the funds go back into the event to create an amazing experience for our attendees.

Beyond Midwest PHP's goal to be the largest PHP conference this year - the included Nomad PHP advertising will help you reach a much larger and broader audience, allowing for follow up advertisements and consistent engagement with the PHP community.


Interested in sponsoring? Check out the prospectus



Next steps

For more information, please visit the Midwest PHP website. The venue, call for papers, and additional information will all be posted there soon.
4238 views · 3 years ago
Using AI for Weather Forecasting

Technology is constantly changing the way we interact, research, and react. One such way artificial intelligence is impacting our daily lives, and we may not even realize it is in weather forecasting.


The forecast we usually have been receiving in our phones and in older times primarily in newspapers, was based on data collected via satellites, radar system and weather balloons. In recent times there has been the addition of IoT based sensors as well. However, with the advent of Artificial Intelligence (AI) finding its way in numerous areas, AI has taken a role in improving the accuracy of weather as well.

The Dataset expansion

A significantly enormous set of data is available - from the weather satellites in space, to the private and government owned weather stations which are gaining real-time data. IBM for instance has more the 0.25 million weather stations that help IBM collect real-time data. Additionally, as we are in the age of Internet of Things (IOT), each small device to big device- cellphones, solar panels and vehicles everything has become or is yet to become yet another data source. Companies like GE have installed IOT street lights, which help in monitoring air quality and humidity. These are some of the few sources which help us in collecting the vast amount of data necessary for building on the AI technology, in future these sources and the amount of available data would grow exponentially.

Google and Weather forecast

Using the AI technology Google is able to develop a weather forecast tool, it has been trained to predict rainfalls accurately as much as six hours before. The underlying technology on which this prediction is build upon is U-Net convolutional neural network which is originally used in biomedical research. It works by taking satellite images as input and uses AI technology to transform these images into high resolution images. The only off-set is this is not real-time prediction and the delay due to complex calculations results in using six-hour old data and hence can only predict six-hours before.

IBM and its efforts in weather prediction

The quest for IBM to venture into weather forecasting began with IBM acquiring The Weather Company. IBM plans on using the large amount of weather data available coupled with IBM Watson and the cloud platform to enhance weather forecasting. In 2019 IBM developed Global High-Resolution Atmospheric Forecasting System (GRAF) in order to forecast weather conditions 12 hours prior to a greater degree of accuracy. The radius encompassed by the GRAF is also more narrowed down up to 3 kilometers as opposed to generally being 10-15 kilometers. Another of its marvel is that it gives accurate predictions down to each hour and not just daily.

Artificial Intelligence and Panasonic

Panasonic is the company behind TAMDAR, the weather sensor installed on commercial airplanes. With this advantage of extensive amount of data from in-flight sensors as well as publicly available data Panasonic developed Global 4D Weather. Proving to their claim of being the most advanced global forecasting platform globally they were able to timely predict Hurricane Irma in its early days.

Uses of Weather Forecasting


Sales

Everyday life decisions are affected by weather, it makes us choose in the way we travel, things we eat and things we buy to wear. The rise in temperature may increase sales of chilled drinks, if the company is fully aware of the forecast it would be able to manage productions as per demand. AI can help brands in maximizing sales based on weather forecasts and in minimizing waste.

Natural Disasters

The Panasonic Global 4D weather predicting Hurricane Irma is just another example where timely prediction can save millions of lives in face of situations like floods and Hurricanes. Companies like IBM combine weather forecasting data with utilities distribution network, which enables them to narrow down areas with likely outages. This enables utilities to place their workforce timely so the repair process catering to damage repairs post disasters is shortened. This in turn brings huge benefits to the overall economy.

Agriculture

The weather and agriculture have the most obvious correlation, each process in farming from sowing to reaping all depends on the weather. As farmers cultivate on huge farming lands, accurate information about each part of the land can help farmers in improving their crops and yield by manifolds. Weather conditions can lead to almost 90 percent of crop losses, 25 percent of these losses can be avoided using accurate AI prediction models to forecast weather and in turn improve the yield.

Transportation

Sea travel has always been eventful, timely prediction of storms by using machine learning techniques and hyper-local data allows companies to plan shipments accordingly and avoid severe weather conditions that usually result in delays. Tools like IBM’s Operations Dashboard for Ground Transportation equips in enhancing productivity based on weather predictions.

Another of the implementation of AI in transportation industry corelating to weather is fuel consumption. For instance, using weather prediction models to reduce airplane fuel consumption during its ascent.

To conclude Artificial Intelligence has a key role to play in weather forecasting, weather direct or indirectly impacts each sector in the economy. As the amount of information available to improve predictions increases exponentially it gives a chance to AI to improve accuracy even further. As we continue narrowing down weather conditions precise to time and location the benefits of such advancements across all industries are innumerable.

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