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Growth stocks have seemed to stop their descent as risk appetite has slowly returned to the market. C3 AI (NYSE:AI) stock was one of those growth plays that have been severely punished by Wall Street for the perceived lackluster results.

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AI stock is down more than 60% from its highs however it seems to have been finding support at the $60 price level. It should open today at about $61.60

I remain bullish on the stock and believe that the company is properly laying the foundation for future growth.

Wall Street Analysts had been disappointed with C3 AIs latest earnings release. This is despite reporting a decrease in net loss and a 26% increase in revenues.

Revenues for fiscal Q4 were $52.3 million, which is an increase from $41.6 million at the same time last year.

As a result of these so-called mixed results, Wedbush reduced the price target of AI stock from $175 to $100.

Canaccord Genuity and Deutsche Bank both reduced their price targets as well from $120 to $75 and $98 to $63 respectively.

These downgrades reflect Wall Streets short-term thinking as C3 AI actually had a few solid wins for the quarter. The company extended its contract with Shell (NYSE:RDS) thus proving the value-add of the companys AI systems.

C3 AI also grew its total number of enterprise customers by 89, an increase of 82% compared to the same time last year.

Despite the earnings miss, C3 AI is continuing to build out its partnership pipeline.

The company recently announced a partnership with data cloud company Snowflake (NYSE:SNOW). This collaboration has the potential to create a value-added service for enterprise clients more than a sum of the individual parts.

Snowflakes cloud data platform generates a ton of data as it runs concurrently across multiple clouds and regions. Enterprise clients can analyze the data generated from those cloud servers using C3 AIs suite of AI products to generate insight that may not be readily apparent.

Remember that C3 AI actually has a suite of pre-built AI applications right out of the gate. This partnership will allow Snowflake customers access to these AI tools without replicating the data thus reducing workload and improving turnaround times.

There are many use cases already for C3 AIs product suite as its tools are being used in industries as wide-ranging as banking to national defense.

Apart from Snowflake, C3 AI also has a strategic partnership with Infor, a cloud-based ERP service provider.

Infor plans to use integrate C3 AIs product offering with its own solutions. The partnership will focus initially on Internet of Things systems but will eventually move to other verticals.

By augmenting our existing Infor product portfolio with prebuilt AI applications from C3 AI that run natively in the cloud, we can expand the Infor portfolio of use cases and further position Infor to capitalize upon the cognitive era, said Infor CEO Kevin Samuelson.

I like that C3 AI is continuing to gather strategic partners in order to sell its AI products. It is also smart of the company to partner with enterprise platforms such as Snowflake and Infor as it will reduce the friction of selling their product.

Enterprise sales typically take a long time and vendors need to go through the corporate bureaucracy before being able to land a sale.

These partnerships effectively ensure that C3 AI has one foot through the door when selling to enterprise clients. It will also ensure that the C3 AI suite is properly integrated with existing clients technology systems thus ensuring a smooth deployment and immediate value-add.

I believe that C3 AI is one of the leaders in the AI space which has massive potential. I fully expect the pace of adoption of AI technology to be slow at the start.

However, I believe adoption could easily hockey-stick in the immediate future. I continue to like C3 AI.

On the date of publication, Joseph Nograles held a LONG position in AI.The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.

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C3 AI Stock Is a Buy on Partnerships and a Likely Sales Pop - InvestorPlace

Its not quite the dystopian headlines dreamed up by George Orwell or Margaret Atwood, but the current attention given to the semiconductor chip shortage is the biggest indicator of our reliance on technology.

The predicted losses from the automotive and IT industries, along with the effects lasting anywhere from six months to two years, paint a picture of over-reliance on computing to push out products. The automotive industry alone is set to lose $110 billion this year, as the chips that power nearly all of the modern cars functionality continue to be unavailable.

Such a loss has naturally gained the attention of the technology industry and has prompted a lot of chief executives to take a guess at how long the shortage will have an effect on manufacturing. However CCS Insight senior director of research, Wayne Lam, says the shortage mainly applies to smaller components that are not on the bleeding edge of technological innovation, but are just as necessary to produce a device.

The shortage is not so much the high ticket chips, the processors, or even memories, it's more benign like power management, or some sort of analogue chipset that isn't necessarily on the bleeding edge of semiconductor technology says Lam.

Those parts are in a bit of a crunch because they are so necessary. It's like buying a brand new car without spark plugs, you just need that one small piece to make it work.

While the chip shortage is being painted as a tech industry apocalypse in some quarters, not all parts of the sector have been affected equally. Ben Stanton, research manager at Canalys, says the mobile industry has experienced a first quarter largely unaffected by the chip shortage, with global analysis firm Counterpoint also reporting a 6% year-on-year increase in European smartphone sales.

Data from Counterpoint found that Samsung and Apple shipments grew 13% and 31% year-on-year respectively, with Xiaomi, Oppo, OnePlus and RealMe all seeing between 73% and 183% growth on the year.

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The chip shortage is certainly having a wide impact across many industries adds Stanton. The smartphone market, though, has actually been fairly resilient, particularly in Q1 when many vendors blew past their quarterly target.

The bottlenecks are there and are having an impact, but they have been slightly overblown and are exacerbated by many vendors now overbooking on component orders to try and secure supply. But if you look at some of the biggest markets, like China, actually the channel was stuffed with inventory by the end of Q1.

Although mobile may be sitting pretty for now, IBM president Jim Whitehurst told the BBC the computer chip shortage could last up to two years and that the industry may need to look into recycling or extending the life of certain computing technologies.

For those looking to upgrade a suite of laptops, IDC manufacturing analyst Maggie Slowik says purchasing decisions will be influenced by availability rather than price.

We've already seen price increases and the forecast is that these products that contain semiconductors will also see prices increase going forward, says Slowik. But we certainly saw with consumer goods, that people are willing to switch very quickly to a different brand, if the particular brand they previously relied on wasnt available.

Businesses have a lot of choice when it comes to office hardware and they can quickly switch brands if a particular product is priced too high, or they have to wait for too long. I think that raises this concept of businesses being more brand agnostic, which makes it hard for manufacturers to retain any loyalty. This chip shortage situation certainly doesn't help at all.

Although the shortage could affect the hardware employees use on a daily basis, Lam and Stanton both say the mass shift to remote working as a result of the pandemic will have alleviated some of the pressure that may have otherwise been felt by businesses.

As organisations move more of their workforce to collaboration platforms, such as Teams, Slack or Webex, an employees ability to do their job is less reliant on the hardware they are using and more affected by whether they have a stable connection to a cloud environment.

For the enterprise market, how youre affected by this shortage is going to depend on where your business is placed. If you're building more cloud servers, that business is going to keep going said Lam. The pandemic has proved that we can productively work virtually and that transition to cloud computing is only going to accelerate; the demand is indisputable.

Digital transformation has accelerated, if anything said Stanton, remote working has forced companies to shift workloads to cloud, and invest in tools to deploy and manage an estate of devices which is decentralised, and no longer exists in a fixed office location.

Going forward, there will be constraints that definitely last until the end of 2021. One important point to note, though, is that lucrative developed regions are being prioritised for device allocation, so the impact of shortages may actually affect areas like Africa, Southeast Asia and Latin America more.

Another interesting nugget I am hearing, particularly in relation to Q2 2021, is that suppressed demand for smartphones in India due to the terrible outbreak of COVID-19 is actually freeing up devices and components to fulfil orders in other markets. So I think the important point is that there are many more regional nuances than people realise. The chip shortage is often painted as a global issue, but the impacts may well be local.

Although it can be seen as an isolated issue, this chip shortage, along with the global pandemic, tremors from changing relationships relating to Brexit and the US and Chinas trade war, as well as global incidents seen in Suez have had huge effects on the supply of products.

Slowik says the main lesson for businesses to learn from the semiconductor chip shortage is not about our reliance on technology. Instead, she implored enterprises to assess their supply chains, making sure they are diverse with distributors they trust, minimising the effect of global events on their business.

Weve been talking about supply chain risk for a long time, but this particular shortage and the pandemic has raised the issue that companies now need to really start looking at further diversifying their supply chains.

One of the hard lessons businesses should have learnt over the past year is that they cannot just assume that there's going to be unlimited supply. They have to build agility into their procurement and supply chain strategies so that they have that additional buffer to freak events, such as the Suez Canal blockage, without having to hoard products.

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How will the semiconductor chip shortage affect enterprise IT? - IT PRO

When Winter Storm Uri cut off its access to grid power, Woodforest National Bank had to enact an emergency data center failover with Zerto.

The massive snowstorm in mid-February created rolling blackouts that shorted out the Houston-based community bank's automatic transfer switch, preventing it from switching over to generator power. This left Woodforest's data center with only UPS battery power, which amounted to about 30 minutes when the issue was discovered.

Luckily, Woodforest has a secondary data center at a colocation facility in Austin, Texas, and immediately began migrating servers over to it. However, at around the 20-minute mark, the Houston building lost power completely. At that point, Woodforest enacted its disaster recovery (DR) plan and used Zerto to fail over the remaining servers to the Austin site.

We had limited people, limited internet, limited power. Marcus LohrIT infrastructure manager, Woodforest National Bank

"We had limited people, limited internet, limited power," said Marcus Lohr, Woodforest National Bank's IT infrastructure manager.

Even under the circumstances, all customer-facing functions, including credit card processing and the website portal, were available within 90 minutes. Within four hours, Woodforest was back to running at full capacity as applications and ancillary business functions were brought back online.

Woodforest's infrastructure was fully tested and prepared for natural disasters, Lohr said. Using Zerto's replication technology, the company had been performing planned migrations between its Houston and Austin sites for the past 12 years.

This two-site setup was initially in response to hurricane season, Lohr said. From July to January, Woodforest would run its servers out of the hardened colocation facility in Austin, and for the rest of the year, the Houston data center would be primary. The two locations alternated between primary and secondary roles every six months, and both locations ran Cisco Unified Computing System on the same hardware.

Zerto serves as Woodforest's primary data protection product for rapid and granular recovery, but it can typically recover only data that's three to seven days old. The bank uses a different backup product for retaining and recovering data that's older than seven days.

Woodforest had refined its DR plan to the point that migrations and failovers have gone from taking a day to down to about an hour, Lohr said. Outside of the technological capabilities provided by Zerto, Woodforest had also worked out a pecking order of who to contact, and all its DR procedures are hosted in a wiki that is accessible even if Woodforest's main site is down.

Additionally, the February outage took place just two weeks after a planned migration, so migration was still relatively fresh on staff members' minds, Lohr said. Despite the fact that only about 25% of the people responsible for DR were available during the winter storm incident, everyone remained calm and knew how to carry out the transition, according to Lohr.

"Twelve years of doing this and trying to make it better, the business has done such a good job with it and nobody lost their heads during this," he said.

In order to prepare for the next big outage, Lohr has started investigating another colocation facility. He said he plans to move all data center activity out of Woodforest's main building, such that both primary and secondary data centers will be in hardened facilities with redundant power, cooling and security year-round.

About 90% of Woodforest's infrastructure is virtualized, but the next step will be to involve cloud more, Lohr said. Woodforest currently has very little cloud infrastructure, with its largest investment being email in the cloud through Office 365.

There are many benefits to the cloud, such as being able to expand Woodforest's DR options, but it's something he needs to approach carefully to ensure he's optimizing costs, Lohr said.

"We're dipping our toes in the cloud right now, but we've been moving towards it. We see it as a tertiary data center in the future," Lohr said.

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Zerto keeps Texas bank from being left in the cold - TechTarget

Not so very long ago, distributed computing meant clustering together a bunch of cheap X86 servers and equipping them with some form of middleware that allowed for work to be distributed across hundreds to thousands to sometimes tens of thousands of nodes. Such scale-out approaches, which added complexity to the software stack, were necessary because normal SMP and NUMA scale up techniques, with very tightly coupled compute and shared memory across a dozen or two nodes, simply could not stretch any further.

These distributed systems, which were difficult enough to build, are childs play compared to what we at The Next Platform are starting to call hyperdistributed systems, which are evolving as disaggregation and composability have entered the imagination of system architects at the same time as a wider and wider variety of compute, memory, storage, and networking components are available and are expected to be used in flexible rather than static ways.

The problem, say the co-founders of a stealth-mode startup called Enfabrica, is that this new hyperdistributed architecture has more bottlenecks than a well-stocked bar. And they say they have developed a combination of silicon, system hardware, and software that will create a new I/O architecture that better suits hyperdistributed systems. Enfabrica is not uncloaking from stealth mode just yet, but the companys founders reached out to us as they were securing their first round of funding $50 million from Sutter Hill Ventures and wanted to elaborate the problems they see in modern distributed systems before they eventually disclose how they have solved those problems.

Enfabrica was formed in 2020 by Rochan Sankar, its chief executive officer, Shrijeet Mukherjee, its chief development officer, plus other founding engineers, and its founding advisor is Christos Kozyrakis, a professor of electrical engineering and computer science at Stanford University for the past two decades who got his PhD in computer science at the University of California at Berkeley with none other than David Patterson as his PhD advisor. Kozyrakis runs the Multiscale Architecture and Systems Team (MAST) at Stanford and has done research stints at Google and Intel, among other organizations; he has done extensive work on vector processors, operating systems, cluster managers for clouds, and transactional memory systems.

Sankar got his bachelors in electrical engineering from the University of Toronto and an MBA from the Wharton School at the University of Pennsylvania and spent seven years at Cypress Semiconductor as an application engineer and chip architect and was notably the director of product marketing and management at Broadcom who drove five generations of its Trident and Tomahawk datacenter switching ASICs, which had over 300 million ports sold and generated billions of dollars in revenue for Broadcom.

Mukherjee got his Masters at the University of Oregon and spent eight years at Silicon Graphics working on high-end graphics systems before joining Cisco Systems as a member of its technical staff and becoming a director of engineering on the groundbreaking California Unified Computing System converged server-network system, specifically working on the virtual interface card that is a predecessor to the DPUs we see emerging today. After that, Mukherjee spent nearly seven years at Cumulus Networks as vice president of software engineering, building the software team that created its open source switch software (now part of the Nvidia stack along with the switch ASICs, NICs, and switch operating systems from the $6.9 billion acquisition of Mellanox Technologies.) When Nvidia bought Cumulus, Mukherjee did a two year stint at Google working on network architecture and platforms and he cant say much more about what he did there, as usual.

Sankar and Mukherjee got to know one another because it was a natural for the leading merchant silicon supplier for hyperscaler and cloud builder switches to get to know the open source network operating system supplier Cumulus needed Broadcom more than the other way around of course. Mukherjee and Kozyrakis worked together during their stints at Google. The team they have assembled the exact number is a secret are system architects and distributed systems engineers that have deployed planetscale software, Mukherjee put it, including people from Amazon Web Services, Broadcom, Cisco Systems, Digital Ocean, Facebook, Google, Intel, and Oracle.

We jointly saw a massive transformation happening in distributed computing, Sankar tells The Next Platform. And that is being keyed by the deceleration of Moores Law and on the fact that Intel has lost the leadership role in setting the pace on server architecture iterations. It is no longer a tick-tock cycle, which then drove all of the corresponding silicon and operating system innovation. That has been completely disrupted by the hyperscalers and cloud builders. And we are now in a race with heterogeneous instances of compute, storage, and networking. where we see a diversity of solutions, cloud sourced processors, other ASICs, GPUs, transcoders, FPGAs, disaggregated flash, potentially disaggregated memory. What we saw happening at the datacenter level in terms of the disaggregation of the architecture and the need for interconnects at the datacenter level is now headed straight into the rack.

It is hard to argue with that, and we dont. We see the same thing happening, and the I/O is way far out of whack with the compute and the storage. Take AI as an example.

AI chips are basically improving their processing capabilities by 10X to 100X, depending on who you believe, says Kozyrakis. At the same time is that systems are becoming bigger. If you look at just hyperscalers, its an order of magnitude increase in the size of datacenters. So we have this massive increase in compute capacity. But we need to provide the 10X, the 100X, the 1000X really, in the I/O connectivity infrastructure. Otherwise, it will be very difficult to bring the benefits of this capacity to bear.

To put it bluntly, hyperscaling was relatively easy if no less impressive for its time, but hyperdistribution is much more complex and it is never going to work without the right I/O. With hyperscaling, says Sankar, distributed systems were built with parent-child query architectures mapped onto homogeneous two-socket X86 server nodes with the same memory and storage and the same network interfaces. The hardware was essentially the same, and that made it all easy and drove volume economics to boot.

Datacenters are evolving into data pipelines, Sankar explains. The diversity of what is happening in the software layer with respect to how data is being processed is mapping into the infrastructure layers, and it is driving increasing heterogeneity in the server architectures to make them optimized. We firmly believe that the solutions that are being sketched out today suffer from problems with scalability and performance, and they suffer from the inability to be best of breed across a wide range of composable architectures.

And without really getting into specifics, Enfabrica says it is building the hardware and software that is going to glue all of this compute, storage, and networking together in a more scalable fashion. We strongly suspect that Enfabrica will borrow some ideas from fast networks and DPUs, but that this is also more than just having a DPU in every server and lashing them together. Pensando, Fungible, Nvidia, and Annapurna Labs within Amazon Web Services are already doing that. And to be frank, what those companies will tell you is that many of the ideas that are in those smart-NICs or DPUs came from the work that Mukherjee did on the virtual network and storage interfaces in the UCS platform. The work Mukherjee did with Cumulus has also figured prominently in the way certain hyperscalers do their networking today, by the way.

Without getting into specifics, since the company is still in stealth mode, Enfabrica thinks it has come up with a better idea for massively distributed I/O.

If you look at all of these companies, they have built a product and now they are going to try to convince people to use them, says Mukherjee. Whereas we assembled a team of people who know what the product needs to do and how it will actually fit in into the lattice of compute, network, and storage that it needs to fit into. This difference actually changes how we emphasize whats hardware and whats software, and where you need to put effort in and where you dont. For example, to make a very illustrative point: how big should a table of something be? Hardware is always going to be limited, software will always want everything to be unlimited. How do you make of those decisions and how do you partition? It requires people who have delivered these kinds of solutions because they understand where people are willing to take a cutback and where absolute line performance matters.

We realize that none of this tells you what Enfabrica is doing. But we can tell you how the company is thinking about I/O in the datacenter and the market sizes and players in these areas that it plans to disrupt. Take a look at this chart we have assembled:

This is what Sankar calls the $10 billion I/O problem that Enfabrica is trying to solve, and that is roughly the total addressable market of all of the silicon for interconnects shown above. This lays out all of the shortcomings of various layers of the interconnect stack.

Whatever Enfabrica is doing, we strongly suspect that it is going to disrupt each of these layers withing the server, within the rack, across the rows, and within the walls of the datacenter. The company is still in stealth mode and is not saying, but we expect to hear more in 2021 and 2022 as it works to intercept a slew of different technologies and scale out systems that are being architected for 2023 and beyond.

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Enfabrica Takes On Hyperdistributed I/O Bottlenecks - The Next Platform