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How to Solve Relationship Problems
Last Updated: July 28, 2022 Approved
Finding solutions, healthy routines.
This article was co-authored by Trudi Griffin, LPC, MS . Trudi Griffin is a Licensed Professional Counselor in Wisconsin specializing in Addictions and Mental Health. She provides therapy to people who struggle with addictions, mental health, and trauma in community health settings and private practice. She received her MS in Clinical Mental Health Counseling from Marquette University in 2011. There are 7 references cited in this article, which can be found at the bottom of the page. wikiHow marks an article as reader-approved once it receives enough positive feedback. In this case, 85% of readers who voted found the article helpful, earning it our reader-approved status. This article has been viewed 403,291 times.
Relationships may develop problems for a variety of reasons, but poor communication is often the reason why some people have a hard time solving these problems. If you are in a relationship that has hit a rough patch, then you may benefit from improving the communication between your partner and yourself. You can also learn how to deal with problems as they arise in order to move past arguments and toward solutions. After things have gotten better, there are things that you can do to ensure that your relationship continues to thrive and grow.
- For example, you could set aside 15 minutes per morning to sit and tell each other about your plans for the day. Or, you could give your partner a call on his or her lunch break to check in and see how your partner’s day is going.
- Scheduling time to talk about relationship problems can be useful as well. By setting a time limit for discussing your problem, you may reduce some of the tension in your relationship and get closer to a solution. For example, you could decide to discuss a specific problem from 7-8pm.
- Keep these conversations as light as possible and avoid discussing anything that might upset your partner during this time. The goal is to get a rapport going again. Of course, if your partner is having a bad day or is feeling stressed about something, listen and be supportive and encouraging.
- Make eye contact with your partner when he or she is talking. Do not look away, look at your phone, or anywhere else when your partner is talking to you. Give your partner your full attention.
- Nod your head and indicate your interest with neutral statements, such as “yes,” “I see,” and “go on.”
- Rephrase what your partner has just said to make sure that you have understood him or her.
- For example, instead of saying, “You never make the bed in the morning,” say, “I would really appreciate it if you could make the bed if you get up after I do.”
- For example, if your partner often loads the dishwasher after dinner and tidies up the kitchen, let him or her know that you value these activities. Say something like, “I just want to say thank you for keeping our kitchen so clean and nice. I appreciate that so much.”
- For example, instead of calling your partner a mean name or insulting him or her in some other way, identify what you want him or her to do.
- For example, you might say something like, “I am sorry for not calling you to tell you that I was going to be late. I will try to be more thoughtful in the future.”
- For example, you may feel that your partner is not helping out around the house as much as he or she should be, and your partner may feel like you are too demanding. Take some time to think about what is bothering you and have your partner do the same.
- For example, you might say, “I have been feeling overwhelmed by the housework and I could use some more help from you.” Your partner might say something like, “I have been feeling overwhelmed as well because of my work schedule and I feel like you don’t appreciate how hard I work.”
- For example, you might say something like, “Okay, I hear what you are saying. I did not realize that you felt that way.”
- Do not get defensive even if your partner responds to you with a defensive claim, such as “You are always nagging me and you never appreciate how hard I work.” Acknowledge your partner’s feelings and move on.
- For example, if your partner has been feeling unappreciated, then you can promise to acknowledge his or her efforts more often. You might also make it a rule that you will not ask you partner to do anything until he or she has had a chance to unwind a bit. Your partner might then promise you that he or she will be more consistent with certain household chores.
- For example, if you promised to take out the garbage every night after dinner, make sure that you do so. Otherwise, your partner may start to feel resentful and begin lapsing on his or her promises as well.
- You don’t need to go far to get away. Try visiting a nearby city for a couple of nights. Go out to a nice dinner, see a play, or visit some museums together.
- For example, you can hold your partner’s hand while watching a movie, give your partner a kiss before you leave for work, or hug your partner before you go to bed each night.
- For example, you might have a girl’s or guy’s night out once per week, take a class by yourself, or join a special interest group on your own.
- For example, you could take a gourmet cooking class together, join a local hiking club, or try to learn a new language together.
- Try to be patient. Solving relationship problems can be a long process, especially if the problems have been going on for a while. Thanks Helpful 3 Not Helpful 0
- Remember to be mature. Jumping to conclusions, screaming at one another, and trying to get revenge is not the way to go. This can lead to more issues in the relationship. Thanks Helpful 2 Not Helpful 0
- You'll need to lower your pride, If you two are having an argument stay calm, Don't let your pride win. This can cause a hard and a worst problem. Try to court again your partner if one of he/she is getting cold in your relationship. Thanks Helpful 3 Not Helpful 0
You Might Also Like
- ↑ http://www.webmd.com/sex-relationships/guide/7-relationship-problems-how-solve-them
- ↑ http://www.helpguide.org/articles/relationships/relationship-help.htm
- ↑ https://www.psychologytoday.com/blog/fixing-families/201101/the-art-solving-relationship-problems
- ↑ https://www.psychologytoday.com/blog/fixing-families/201311/common-sense-approach-solving-relationship-problems
- ↑ http://www.webmd.com/sex-relationships/guide/7-relationship-problems-how-solve-them?page=3
- ↑ http://www.webmd.com/sex-relationships/guide/7-relationship-problems-how-solve-them?page=2
- ↑ http://psychcentral.com/lib/how-can-i-improve-intimacy-in-my-marriage/
About This Article
The best way to solve relationship problems is by improving communication. You can start by scheduling time for you and your loved one to just sit down and talk. For example, you could spend a few minutes in the morning to tell each other about your daily plans. When you think you're ready to move onto discussing the relationship, try to have your conversations in a public place to keep things civil. For more relationship advice from our reviewer, like how to maintain your relationship once things improve, keep reading. Did this summary help you? Yes No
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Our next-generation model: Gemini 1.5
Feb 15, 2024
The model delivers dramatically enhanced performance, with a breakthrough in long-context understanding across modalities.
A note from Google and Alphabet CEO Sundar Pichai:
Last week, we rolled out our most capable model, Gemini 1.0 Ultra, and took a significant step forward in making Google products more helpful, starting with Gemini Advanced . Today, developers and Cloud customers can begin building with 1.0 Ultra too — with our Gemini API in AI Studio and in Vertex AI .
Our teams continue pushing the frontiers of our latest models with safety at the core. They are making rapid progress. In fact, we’re ready to introduce the next generation: Gemini 1.5. It shows dramatic improvements across a number of dimensions and 1.5 Pro achieves comparable quality to 1.0 Ultra, while using less compute.
This new generation also delivers a breakthrough in long-context understanding. We’ve been able to significantly increase the amount of information our models can process — running up to 1 million tokens consistently, achieving the longest context window of any large-scale foundation model yet.
Longer context windows show us the promise of what is possible. They will enable entirely new capabilities and help developers build much more useful models and applications. We’re excited to offer a limited preview of this experimental feature to developers and enterprise customers. Demis shares more on capabilities, safety and availability below.
Introducing Gemini 1.5
By Demis Hassabis, CEO of Google DeepMind, on behalf of the Gemini team
This is an exciting time for AI. New advances in the field have the potential to make AI more helpful for billions of people over the coming years. Since introducing Gemini 1.0 , we’ve been testing, refining and enhancing its capabilities.
Today, we’re announcing our next-generation model: Gemini 1.5.
Gemini 1.5 delivers dramatically enhanced performance. It represents a step change in our approach, building upon research and engineering innovations across nearly every part of our foundation model development and infrastructure. This includes making Gemini 1.5 more efficient to train and serve, with a new Mixture-of-Experts (MoE) architecture.
The first Gemini 1.5 model we’re releasing for early testing is Gemini 1.5 Pro. It’s a mid-size multimodal model, optimized for scaling across a wide-range of tasks, and performs at a similar level to 1.0 Ultra , our largest model to date. It also introduces a breakthrough experimental feature in long-context understanding.
Gemini 1.5 Pro comes with a standard 128,000 token context window. But starting today, a limited group of developers and enterprise customers can try it with a context window of up to 1 million tokens via AI Studio and Vertex AI in private preview.
As we roll out the full 1 million token context window, we’re actively working on optimizations to improve latency, reduce computational requirements and enhance the user experience. We’re excited for people to try this breakthrough capability, and we share more details on future availability below.
These continued advances in our next-generation models will open up new possibilities for people, developers and enterprises to create, discover and build using AI.
Context lengths of leading foundation models
Highly efficient architecture
Gemini 1.5 is built upon our leading research on Transformer and MoE architecture. While a traditional Transformer functions as one large neural network, MoE models are divided into smaller "expert” neural networks.
Depending on the type of input given, MoE models learn to selectively activate only the most relevant expert pathways in its neural network. This specialization massively enhances the model’s efficiency. Google has been an early adopter and pioneer of the MoE technique for deep learning through research such as Sparsely-Gated MoE , GShard-Transformer , Switch-Transformer, M4 and more.
Our latest innovations in model architecture allow Gemini 1.5 to learn complex tasks more quickly and maintain quality, while being more efficient to train and serve. These efficiencies are helping our teams iterate, train and deliver more advanced versions of Gemini faster than ever before, and we’re working on further optimizations.
Greater context, more helpful capabilities
An AI model’s “context window” is made up of tokens, which are the building blocks used for processing information. Tokens can be entire parts or subsections of words, images, videos, audio or code. The bigger a model’s context window, the more information it can take in and process in a given prompt — making its output more consistent, relevant and useful.
Through a series of machine learning innovations, we’ve increased 1.5 Pro’s context window capacity far beyond the original 32,000 tokens for Gemini 1.0. We can now run up to 1 million tokens in production.
This means 1.5 Pro can process vast amounts of information in one go — including 1 hour of video, 11 hours of audio, codebases with over 30,000 lines of code or over 700,000 words. In our research, we’ve also successfully tested up to 10 million tokens.
Complex reasoning about vast amounts of information
1.5 Pro can seamlessly analyze, classify and summarize large amounts of content within a given prompt. For example, when given the 402-page transcripts from Apollo 11’s mission to the moon, it can reason about conversations, events and details found across the document.
Gemini 1.5 Pro can understand, reason about and identify curious details in the 402-page transcripts from Apollo 11’s mission to the moon.
Better understanding and reasoning across modalities
1.5 Pro can perform highly-sophisticated understanding and reasoning tasks for different modalities, including video. For instance, when given a 44-minute silent Buster Keaton movie , the model can accurately analyze various plot points and events, and even reason about small details in the movie that could easily be missed.
Gemini 1.5 Pro can identify a scene in a 44-minute silent Buster Keaton movie when given a simple line drawing as reference material for a real-life object.
Relevant problem-solving with longer blocks of code
1.5 Pro can perform more relevant problem-solving tasks across longer blocks of code. When given a prompt with more than 100,000 lines of code, it can better reason across examples, suggest helpful modifications and give explanations about how different parts of the code works.
Gemini 1.5 Pro can reason across 100,000 lines of code giving helpful solutions, modifications and explanations.
When tested on a comprehensive panel of text, code, image, audio and video evaluations, 1.5 Pro outperforms 1.0 Pro on 87% of the benchmarks used for developing our large language models (LLMs). And when compared to 1.0 Ultra on the same benchmarks, it performs at a broadly similar level.
Gemini 1.5 Pro maintains high levels of performance even as its context window increases. In the Needle In A Haystack (NIAH) evaluation, where a small piece of text containing a particular fact or statement is purposely placed within a long block of text, 1.5 Pro found the embedded text 99% of the time, in blocks of data as long as 1 million tokens.
Gemini 1.5 Pro also shows impressive “in-context learning” skills, meaning that it can learn a new skill from information given in a long prompt, without needing additional fine-tuning. We tested this skill on the Machine Translation from One Book (MTOB) benchmark, which shows how well the model learns from information it’s never seen before. When given a grammar manual for Kalamang , a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person learning from the same content.
As 1.5 Pro’s long context window is the first of its kind among large-scale models, we’re continuously developing new evaluations and benchmarks for testing its novel capabilities.
For more details, see our Gemini 1.5 Pro technical report .
Extensive ethics and safety testing
In line with our AI Principles and robust safety policies, we’re ensuring our models undergo extensive ethics and safety tests. We then integrate these research learnings into our governance processes and model development and evaluations to continuously improve our AI systems.
Since introducing 1.0 Ultra in December, our teams have continued refining the model, making it safer for a wider release. We’ve also conducted novel research on safety risks and developed red-teaming techniques to test for a range of potential harms.
In advance of releasing 1.5 Pro, we've taken the same approach to responsible deployment as we did for our Gemini 1.0 models, conducting extensive evaluations across areas including content safety and representational harms, and will continue to expand this testing. Beyond this, we’re developing further tests that account for the novel long-context capabilities of 1.5 Pro.
Build and experiment with Gemini models
We’re committed to bringing each new generation of Gemini models to billions of people, developers and enterprises around the world responsibly.
Starting today, we’re offering a limited preview of 1.5 Pro to developers and enterprise customers via AI Studio and Vertex AI . Read more about this on our Google for Developers blog and Google Cloud blog .
We’ll introduce 1.5 Pro with a standard 128,000 token context window when the model is ready for a wider release. Coming soon, we plan to introduce pricing tiers that start at the standard 128,000 context window and scale up to 1 million tokens, as we improve the model.
Early testers can try the 1 million token context window at no cost during the testing period, though they should expect longer latency times with this experimental feature. Significant improvements in speed are also on the horizon.
Developers interested in testing 1.5 Pro can sign up now in AI Studio, while enterprise customers can reach out to their Vertex AI account team.
Learn more about Gemini’s capabilities and see how it works .
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David Bell Has a Problem Any Manager Would Love to Solve
The Reds have had many problems over their long and convoluted history, but few so wonderful as this: They have more good infielders than they can use. And not just good, but young, and mostly on pre-arbitration deals. The oldest and most expensive, Jeimer Candelario , they’ve just signed to a three-year, $45 million contract. He’s only 30, and coming off a season in which he posted a 117 wRC+.
The other six guys include a recent rookie of the year, Jonathan India , and five talented youngsters age 26 or younger: Spencer Steer , Elly De La Cruz , Matt McLain , Christian Encarnacion-Strand , and Noelvi Marte . Steer had a cameo at the end of 2022, but the other four got their first taste of major league action last year and performed somewhere between competently and superbly.
Here’s the sum total, with each player’s stats from last season:
Reds manager David Bell addressed the media on Tuesday, and sure enough the topic of this glut of young talent came up . How he works this problem through will be the most interesting part of the Reds’ season — perhaps the most interesting storyline in the entire NL Central.
Bell is entering his sixth season as Reds manager, and in that time he’s never finished more than four games over .500 with a series of mostly underfunded rosters. He’s made the playoffs only once, in 2020; that year, the Reds were the no. 7 seed in the only season in baseball history in which that would’ve been good enough for a playoff berth. Once there, they got swept by the Braves in the first round, and didn’t even manage to score a run in the process.
But last season, buoyed largely by this same exciting crop of infielders, the Reds were in the playoff race well into late September. With no obvious runaway favorite for the division title, Cincinnati enters the season with more serious playoff aspirations than in any year of Bell’s tenure to this point.
If not for the pressure to win now, Bell could privilege his younger, higher-upside infielders in the battle for playing time, with no fear of negative repercussions. Arguably, that’s what he did with De La Cruz last season, even tough the gigantic shortstop tired and struggled down the stretch.
Now, Bell has to balance playing time for seven players who need to fit into six spots in the lineup. And he needs to do it while maximizing his odds of winning each game, while at the same time not compromising the development of his young players, especially De La Cruz, who will need to work through their struggles in order to reach their ultimate ceilings.
It’ll be a tricky balance to strike, unless one of four things happens. In increasing order of likelihood:
1. The Reds lobby MLB to change the rules to place a fourth base on the infield between now and Opening Day, opening a spot in the lineup.
2. The Reds’ R&D department’s years of research into subquantum kinetics and temporal mechanics finally bear fruit in the form of a working time machine, which Bell uses to travel back to 2018 and convince India to learn how to play catcher.
3. One of the players involved gets traded. God knows the Reds tried to move India, but now that he’s been signed to a two-year contract extension, it seems that ship is at least in the process of sailing.
4. Someone gets hurt or stops hitting. It’d make the Reds worse, but it’d make filling out the lineup card easier. Marte is already recovering from an offseason hamstring injury, but I’d be astonished if he isn’t ready to go Opening Day.
There is good news. Everyone in the Reds’ infield rotation can play multiple positions, and there are multiple players who can cover every infield position. The Reds also don’t have an entrenched, incumbent designated hitter or a regular left fielder from outside this crop of players. And by spreading seven players across six positions — the four infield spots, DH, and left field — the Reds can give everyone a starter’s playing time. Last season, Cincinnati allocated a total of 4,134 plate appearances to those six positions. Split seven ways, that’s 590 PA and change.
So how do those plate appearances get divided up?
Let’s start with what Bell and president of baseball ops Nick Krall actually said . De La Cruz will be the everyday shortstop, which is logical. Last year, he was the worst hitter of these seven players statistically, but given that De La Cruz also posted a maximum exit velocity of 119.2 mph, the hope is that he doesn’t stay that way for long. Even if he does remain a mid-80s wRC+ hitter, De La Cruz has the tools — excellent range and one of the best throwing arms in the sport at any position — to carry that level of offense and still be an average-or-better shortstop.
The Reds should give De La Cruz all the playing time he can handle, because he’s the best defender at the hardest position, and would benefit most from reps. McLain will start at second and spell De La Cruz at short; he was the team’s best all-around infielder last year, and has earned a starter’s playing time.
Steer, who played 45 games in the outfield in 2023, will play in the outfield corners. And roping him in (I’m sorry, I couldn’t help it) with this group will open up an additional spot in the lineup. Steer played more games at first base than anywhere else in 2023, and is also capable of playing at second and third, though I doubt he’d be needed much there.
The one drawback to using this group to fill in left field: Encarnacion-Strand has played 10 innings in the outfield in his professional career. Apart from Steer, that’s the totality of this group’s professional outfield experience. But in general, anyone who can play second or third can probably hack it in left, and both Encarnacion-Strand and India are going to get some outfield reps in spring training.
India has actually never played anywhere but second base in the major leagues, which surprised me, but he played a ton of third base in college and filled in at shortstop from time to time in the minors. If he can develop into a legitimate utilityman, capable of playing second base and the four corners, he’ll find his way into plenty of games.
There are two further considerations, which weren’t reported as part of Krall and Bell’s comments on Tuesday: Candelario is going to play every day. Nobody signs a $15 million-a-year, multi-year contract to be part of a platoon, particularly not with a team that doesn’t give out many $15 million-a-year contracts to begin with. And Marte should get preferential treatment in terms of playing time. Just as with De La Cruz, younger, inexperienced players need to play consistently in order to develop.
So based on those considerations, here’s how the Reds ought to line up. This is basically the working assumption on our depth charts at RosterResource as well:
The challenge for Bell, then, will be picking the spots to insert Encarnacion-Strand and India into the lineup. Let’s look at how everyone stacks up in terms of platoon advantage:
I’ve included Marte’s minor league numbers not because I think his experience at Double-A is comparable to the other players’ major league competition, but because he only played 35 games in the majors and it’s hard to tell anything about a player’s tendencies in that small a sample.
Here’s what we can tell: Candelario is basically the same from both sides of the plate, while De La Cruz as pretty good against righties but hit like a pitcher against lefties. Again, the Reds shouldn’t hide him or platoon him, because they need him to develop, but maybe Bell could go out of his way to rest De La Cruz against tough left-handed opponents.
Among the right-handed hitters, Steer and McLain both had substantial platoon splits in 2023 but hit righties well enough to start. Encarnacion-Strand and India both had reverse platoon splits in the majors in 2023, which would be convenient considering the Reds don’t have any strictly left-handed-hitting infielders. Zooming out to a multi-year sample, India’s reverse split persists — for his career, he has a 99 wRC+ against lefties but 110 against righties. But if Encarnacion-Strand gets to count his minor league numbers, like Marte did, his platoon split basically zeroes out.
So if De La Cruz sits when someone like Max Fried or Blake Snell comes to town, maybe Encarnacion-Strand gets into the lineup at DH or a corner, with everyone else sliding down the defensive spectrum and McLain ending up at shortstop.
The other situational consideration to monitor is offense versus defense. We know that De La Cruz is the team’s best defensive shortstop. We know that if De La Cruz is at short, McLain is the best defensive second baseman. To be honest, he might be the best second baseman anyway, because putting De La Cruz’s arm that close to first base might be legitimately dangerous.
Beyond that, it’s a bit of a crapshoot. Marte and Encarnacion-Strand are inexperienced at the major league level, and India is inexperienced at first base and in left field. Candelario has traditionally been an average defender at both corners. He’s had a couple above-average seasons in his youth, and is better at third than first, though that might change with age and experience.
The only relative judgment I feel comfortable making, apart from De La Cruz and McLain, is that Steer is a horrendous defender anywhere you put him. Here are his defensive numbers from his season-and-change in the majors:
I don’t think you can actually learn that much by watching spring training games generally, but anyone who’s interested in the Reds’ long-term success should be glued to the TV whenever India is in the outfield. He’s graded out as a pretty poor defender at second base in his major league tenure, but if he shows any kind of aptitude in left field — enough to force Steer into more of a full-time DH role — that’d clarify Cincinnati’s logjam pretty quickly.
Balancing short- and long-term team goals while keeping all seven players happy is going to take some doing, but that’s why Bell gets paid the big bucks. Besides, there are at least a dozen other managers across the league who would love to have a chance to solve a problem like this. I’m sure he’ll figure it out.
Michael is a writer at FanGraphs. Previously, he was a staff writer at The Ringer and D1Baseball, and his work has appeared at Grantland , Baseball Prospectus , The Atlantic , ESPN.com, and various ill-remembered Phillies blogs. Follow him on Twitter, if you must, @MichaelBaumann .
As someone who follows the Reds very closely, this is a good piece that mostly gets things right. I do think there are two issues, though:
I have not seen anyone anywhere from within the Reds say that India is going to play 3rd. My understanding is that he doesn’t have the arm for it. They tried to fix him in the minors and he couldn’t make the adjustment to be an MLB 3B. If there is a day when neither of the first two options are available, I’d be shocked if the third option wasn’t EDLC with McLain sliding over to short for the day.
Additionally, I think any confidence about what kind of defender Steer is has little merit. He played four different positions last year, as a rookie. Two of which he hadn’t really played before. The sample size just isn’t there. And the scouting I saw from his time in the minors didn’t characterize him as a disastrous defender. It will be interesting to see if he improves with a regular position.
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Heavy Machinery Meets AI
- Vijay Govindarajan
- Venkat Venkatraman
Until recently most incumbent industrial companies didn’t use highly advanced software in their products. But now the sector’s leaders have begun applying generative AI and machine learning to all kinds of data—including text, 3D images, video, and sound—to create complex, innovative designs and solve customer problems with unprecedented speed.
Success involves much more than installing computers in products, however. It requires fusion strategies, which join what manufacturers do best—creating physical products—with what digital firms do best: mining giant data sets for critical insights. There are four kinds of fusion strategies: Fusion products, like smart glass, are designed from scratch to collect and leverage information on product use in real time. Fusion services, like Rolls-Royce’s service for increasing the fuel efficiency of aircraft, deliver immediate customized recommendations from AI. Fusion systems, like Honeywell’s for building management, integrate machines from multiple suppliers in ways that enhance them all. And fusion solutions, such as Deere’s for increasing yields for farmers, combine products, services, and systems with partner companies’ innovations in ways that greatly improve customers’ performance.
Combining digital and analog machines will upend industrial companies.
Idea in Brief
Until recently most incumbent industrial companies didn’t use the most advanced software in their products. But competitors that can extract complex designs, insights, and trends using generative AI have emerged to challenge them.
Industrial companies must develop strategies that fuse what they do best—creating physical products—with what digital companies do best: using data and AI to parse enormous, interconnected data sets and develop innovative insights.
The Changes Required
Companies will have to reimagine analog products and services as digitally enabled offerings, learn to create new value from data generated by the combination of physical and digital assets, and partner with other companies to create ecosystems with an unwavering focus on helping customers solve problems.
For more than 187 years, Deere & Company has simplified farmwork. From the advent of the first self-scouring plow, in 1837, to the launch of its first fully self-driving tractor, in 2022, the company has built advanced industrial technology. The See & Spray is an excellent contemporary example. The automated weed killer features a self-propelled, 120-foot carbon-fiber boom lined with 36 cameras capable of scanning 2,100 square feet per second. Powered by 10 onboard vision-processing units handling almost four gigabytes of data per second, the system uses AI and deep learning to distinguish crops from weeds. Once a weed is identified, a command is sent to spray and kill it. The machine moves through a field at 12 miles per hour without stopping. Manual labor would be more expensive, more time-consuming, and less reliable than the See & Spray. By fusing computer hardware and software with industrial machinery, it has helped farmers decrease their use of herbicide by more than two-thirds and exponentially increase productivity.
- Vijay Govindarajan is the Coxe Distinguished Professor at Dartmouth College’s Tuck School of Business, an executive fellow at Harvard Business School, and faculty partner at the Silicon Valley incubator Mach 49. He is a New York Times and Wall Street Journal bestselling author. His latest book is Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future . His Harvard Business Review articles “ Engineering Reverse Innovations ” and “ Stop the Innovation Wars ” won McKinsey Awards for best article published in HBR. His HBR articles “ How GE Is Disrupting Itself ” and “ The CEO’s Role in Business Model Reinvention ” are HBR all-time top-50 bestsellers. Follow him on LinkedIn . vgovindarajan
- Venkat Venkatraman is the David J. McGrath Professor at Boston University’s Questrom School of Business, where he is a member of both the information systems and strategy and innovation departments. His current research focuses on how companies develop winning digital strategies. His latest book is Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future. Follow him on LinkedIn . NVenkatraman
How do you solve a problem like a gopher? Fountain Valley is learning through experience
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How do you solve a problem like a gopher? In the city of Fountain Valley, rodents digging networks of subterranean tunnels that compromise the soil integrity of local parklands have been an ongoing challenge for public works employees.
“They burrow all day long, so there are shallow tunnels that can create risks if they do cave in,” said Mark Sprague, a field services manager for the city. “They mostly feed on the roots of plants. They also chew irrigation lines. It’s caused a lot of problems both privately and publicly.”
Visitors to Los Alamos Park, Harper Park and the city’s Sports Park near Mile Square Regional Park — identified by city staff as gopher “hot spots” — may have seen signs of the rodent’s presence in the area, including cones and markers placed near tunnels.
Officials have for years contracted with an area landscaping company to trap and remove the critters. But recently, an observed increase in gopher activity is popping up in residential neighborhoods.
Fountain Valley City Councilman Jim Cunneen said it’s common for residents to air gopher grievances at City Hall, sometimes speaking in public comments at council meetings, or to bring up the subject at local functions.
“It’s not unique to our city, but something has triggered a rise in the population of gophers in our parks,” he said Friday. “A lot of people in our neighborhood are dealing with gophers. You can see it in some of the front lawns of our neighbors.”
Cunneen has lived for the past three decades near the city’s Los Alamos Park on a street named La Marmota Avenue, the Spanish word for groundhog. Although he recalled having issues with the animals in the ’90s, his backyard was pretty calm until the recent population explosion.
“We have at least 30 holes gophers have chewed,” he said. “They take out a 3- to 4-inch diameter patch, and they’re also burrowing so the surface becomes uneven — it’s horrible.”
Gopher Mitigation Update https://t.co/zG5HUgmcwh pic.twitter.com/Njt8PAPLOr — City of Fountain Valley (@fv_cityhall) February 7, 2024
City officials reported last week on social media gopher mitigation efforts are in full swing at local parks. Where a typical month may bring in 15 to 20 animals, last month more than 40 trappings were logged, according to Sprague.
Cunneen said extermination companies tend not to deal with gophers, requiring residents to seek out services that offer to remove the animals by trapping them. It’s unclear, however, what happens once an animal is captured.
Representatives of Merchants Landscape Services, which handles landscaping for Fountain Valley and its more than 150 acres of park space under an $873,000 annual contract, did not immediately respond to a request for that information. But one local wildlife expert offered some advice.
Debbie McGuire, executive director of the nonprofit Wetlands & Wildlife Care Center in Huntington Beach, maintains state laws prohibit the relocation of many small animals and rodent species into different habitats. She said many removal companies end up humanely euthanizing the animals they trap.
One explanation for the rising gopher population may be a decline in the presence of predators who feed on them, such as bobcats and coyotes or birds of prey like barn owls.
“Gophers are really important for the ecosystem. They move the soil around and keep roots aerated so plants stay healthy,” McGuire said Friday. “But there are times when there are no predators to keep their population down, and they’ll get out of control.”
She suggested city employees or residents in Fountain Valley might look into installing nesting boxes in public parks and residential neighborhoods to attract animals like the barn owl, which prey on gophers but leave larger animals, like cats and dogs, undisturbed.
A number of organizations and resources can be found online, including the Barn Owl Box Co. , which sells nesting boxes and instructs people how to build their own.
“The best thing is to leave nature alone and let the circle of life take care of things,” McGuire advised.
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Sara Cardine covers the city of Costa Mesa for the Daily Pilot. She comes from the La Cañada Valley Sun, where she spent six years as the news reporter covering La Cañada Flintridge and recently received a first-place Public Service Journalism award from the California News Publishers Assn. She’s also worked at the Pasadena Weekly, Stockton Record and Lodi-News Sentinel, which instilled in her a love for community news. (714) 966-4627