Here’s a look at some of the reviews that have already been released for the film, including CNET’s own.
The sequel trap
“While It Chapter 2 brings their story to a conclusive and largely satisfying end, it disappointingly walks right into the same trap as many sequels. Bloated with story ideas, characters and, most noticeably, running time — not to mention excessive CGI — Chapter 2 is at times harder to hang onto than an escaping balloon.” — Jennifer Bisset, CNET
Kudos for the cast
“The casting of the grown up versions of each character is very impressively done, with James McAvoy and Jay Ryan seeming to be the standouts — but that might be because their characters bear the most striking resemblance to their younger counterparts. Meanwhile, Bill Hader pours an impressive amount of heart into the film, despite being forced to try to add the comic relief endlessly, a task which lands most of the time.” — Brandon Davis, ComicBook.com
First film was better
“The decision [to split the book into two movies] paid off beautifully for Chapter 1, transforming the cerebral novel into a Goonies-flavored coming-of-age adventure with a cast of magnetic, scrappy, lovable kids who faced off against a monster and learned all sorts of lessons about life, love, and friendship along the way. In Chapter 2, however, the cracks in the concept begin to show, and ultimately, the final chapter fails to maintain the spark of the first, succumbing to a dangerous cocktail of muddled timelines, poorly placed novel call-backs, and scattered focus.” — Meg Downey, GameSpot.com
Nearly three hours is too long
“So what’s the problem? For starters, It: Chapter Two is an ass-numbing two hours and 50 minutes. That’s a good half-hour longer than Chapter One, proving the adage that less is definitely more. The dragging pace diminishes the film’s ability to hold us in its grip. There are endless flashbacks to the characters as kids, as if director Andy Muschietti and screenwriter Gary Dauberman didn’t trust the audience to have seen the first film and decided to squeeze the highlights into this one just in case.” — Peter Travers, Rolling Stone
Trailers and teasers
A featurette released in early September includes some of the stars briefly talking about their roles.
For many companies, the network is like a creepy haunted house—there’s darkspace around every corner and they know bad stuff is hiding there, but they can’t see it until it’s too late. The first step to solving this problem is to understand what we mean by “darkspace” and why every organization with a digital presence should be thinking about these issues. We’ll start there, and then look at a new category of product emerging to help IT and SecOps shed light into the darkspace so they can fight the monsters hiding there……..
Red Hat was up for sale for quite some time, according to some sources. Several potential buyers passed on the opportunity, including Google. But not IBM. IBM paid big bucks for the open source software solutions company. At a price tag of $33 Billion. That makes Red Hat valued at one-third of IBM’s current market cap, and more than twice Big Blue’s cash chest. What did IBM see in Red Hat that others are missing? Simple. A strategic fit that could help the technology giant expand into emerging segments of the IT industry, and turn its fortunes around…….
Thirty-eight percent of CFOs are responsible for IT departments, but many finance departments operate separately from their IT counterparts. As CFO duties evolve to include greater technology responsibilities, it is vital for modern finance departments to prioritize a data strategy. In fact, digital transformation is a necessity. Without evolving the relationship between finance and IT to prioritize data and actionable insights, your business risks falling behind competitors and achieving full potential……
Compared to a classic IT solution, [partnership] enables you to go much further along the way in a short period of time,” Carlo Schots, from The Netherlands-based IT service provider Ordina, stated in a video shown at SAP Leonardo Now last month. “Together they enable you to innovate digitally.” Ordina partnered with SAP to help Brussels-based telecom Proximus expand its fiberoptic network, shipping materials from a central warehouse to contractors and subcontractors spread across the country. Proximus used some of SAP Leonardo’s intelligent technologies to…….
More and more of us are living in smart, connected homes. We use devices like Amazon’s Alexa to control our lights, Google’s Nest to learn and anticipate our heating preferences, and smart meters to give us real-time data about our energy usage.
But these Internet of Things technologies have an impact far beyond our homes, especially when it comes to energy.
Smart meters, for example, give a clearer picture of energy usage not only to consumers, but to grid operators too, taking the guesswork out of balancing supply and demand.
And this is just the tip of the iceberg when it comes to the digital infrastructure now helping the energy sector to be more efficient than ever before.
Smarter supply with AI
If you visit a modern power plant, you will find digital sensors attached to every piece of equipment.
These sensors generate vast amounts of data, which Artificial Intelligence is able to analyze and make sense of to increase efficiency – helping to generate more electricity from less fuel.
Not only this, but combining data and AI can create a power plant capable of operating itself.
And this is not just a futuristic vision. In Takasago, Japan, Mitsubishi Heavy Industries Group is in the process of building a ground-breaking new natural gas power plant capable of running autonomously.
The plant uses a digital platform developed by Mitsubishi Hitachi Power Systems, MHPS-Tomoni. This has the capability to mine data generated by sensors around the plant, and uses AI to take on tasks such as diagnosing failures before they happen, reducing supply when needed, or increasing power generation if demand spikes.
While the plant can be fully independent, the concept of Tomoni – which translates as ‘together with’ – emphasises the importance of AI and experienced engineers working together to make power plants operate as efficiently as possible.
Though the new Takasago facility is still under construction, operational plants are already using the system to improve their performance. One gas-fired power plant in Oklahoma, USA, using MHPS’s digital platform has set a global 60 hertz combined-cycle efficiency record of 62%.
In addition, ongoing surveillance of sensor data and AI-driven analytics can help plant operators detect potential problems early and take action. This surveillance can take place anywhere, via the cloud. MHPS has calculated that they can typically reduce downtime by three days per incident as a result.
Data driving down demand
While it is a significant step forwards, using AI to run power plants more efficiently only solves the supply side of the wider energy efficiency equation.
Reducing energy demand is also critical, and huge leaps forwards have been made over the past decade.
According the International Energy Agency, global energy intensity – measured as the amount of primary energy demand needed to produce one unit of GDP – fell by 1.8% in 2016. Since 2010, intensity has declined at an average rate of 2.1% per year, which is a significant improvement from the average rate of 1.3% between 1970 and 2010.ore than half of these gains have come through the improved HVAC systems and energy efficiency of buildings. This is thanks to everything from advanced building insulation, energy efficient lightbulbs through to devices like smart thermostats.
But industrial energy – the biggest and most intensive area of energy consumption – has so far only accounted for around a sixth of the total global investment in energy efficiency.
Despite these relatively low levels of spending compared to buildings and transport, the IEA says energy use per unit of economic output in the industrial sector fell by nearly 20% between 2000 and 2016.
The IEA says this trend is likely to continue thanks to the growing use of energy management systems, which provide a structure to monitor and control energy consumption and identify opportunities to improve efficiency.
These industrial-scale systems connect with IoT sensors and use AI to analyse the data that they generate and provide actionable insights.
Through data visualisations, factory owners can get a clear understanding of their energy use, and even identify which pieces of equipment are running inefficiently. Poor calibration or potential faults are among the triggers that signal a piece of equipment may need to be repaired.
Factory owners can also see the patterns in their energy usage that may help them identify the best times to operate certain functions, cutting costs and increasing efficiency.
In some countries, such as the US and UK, for example, major energy users can even use this knowledge to participate in so-called ‘demand side response programs’ in the local electricity markets. In these markets energy consumption can be traded as virtual generating capacity.
This effectively means they are paid not to operate during times of peak electricity demand. It also helps grid operators make sure there is always enough electricity to keep the lights on.
A leading industrial firm, Mitsubishi Heavy Industries Group (40 billion USD annual revenue) is finding new, simpler and sustainable ways to power cities, improve infrastructure, innovate manufacturing and connect people and ideas around the globe with ever-increasing speed and efficiency. For over 130 years, the company has channeled big thinking into innovative and integrated solutions that move the world forward. MHI owns a unique business portfolio covering land, sea, sky and even space across industries from commercial aviation and transportation to power plants and gas turbines, and from machinery and infrastructure to integrated defense and space systems. Visit MHI Global or MHI Spectra.